Remote physiologic parameter determination methods and platform apparatuses

ABSTRACT

Certain aspects of the disclosure are directed to an apparatus including a scale and external circuitry. The scale includes a platform for a user to stand on, and data-procurement circuitry for collecting signals indicative of the user&#39;s identity and cardio-physiological measurements while the user is standing on the platform. The scale includes processing circuitry to process data obtained by the data-procurement circuitry and therefrom generate cardio-related physiologic data, and an output circuit to send user data from the scale for reception at a remote location. The external circuitry receives and validates the user data as concerning a specific user associated with a user ID and determine at least one physiologic parameter of the user using the user data. Further, the external circuitry derives additional health information corresponding to the user data based on categories of interest and outputs the additional health information to the scale for display.

RELATED APPLICATION DATA

This application is related to PCT Application (Ser. No.PCT/US2016/062484), entitled “Scale-Based Parameter Acquisition Methodsand Apparatuses”, filed on Nov. 17, 2016, PCT Application (Ser. NoPCT/US2016/062505), entitled “Remote Physiologic Parameter AssessmentMethods and Platform Apparatuses”, filed on Nov. 17, 2016, U.S.Provisional Application (Ser. No. 62/258,253), entitled “InitializationMethod and Devices and User Physiological Platforms”, filed Nov. 20,2015, U.S. Provisional Application (Ser. No 62/260,174), entitled“Remote Physiological Parameter Determination Methods and PlatformApparatuses”, filed Nov. 25, 2015, and U.S. Provisional Application(Ser. No. 62/266,523) entitled “Social Grouping Using a User-SpecificScale-Based Enterprise System”, filed Dec. 11, 2015”, which are fullyincorporated herein by reference.

Overview

Various aspects of the present disclosure are directed toward methods,systems and apparatuses that are useful in remotely determining aphysiologic parameter of a user using user data obtained by a scale.

Various aspects of the present disclosure are direct toward monitoring avariety of different physiological characteristics for many differentapplications. For instance, physiological monitoring instruments areoften used to measure a number of patient vital signs, including bloodoxygen level, body temperature, respiration rate and electrical activityfor electrocardiogram (ECG) or electroencephalogram (EEG) measurements.For ECG measurements, a number of electrocardiograph leads may beconnected to a patient's skin, and are used to obtain a signal from thepatient.

Obtaining physiological signals (e.g., data) can often require specialtyequipment and intervention with medical professionals. For manyapplications, such requirements may be costly or burdensome. These andother matters have presented challenges to monitoring physiologicalcharacteristics.

Various aspects of the present disclosure are directed towardmultisensory biometric devices, systems and methods. Aspects of thepresent disclosure include user-interactive platforms, such as scales,large and/or full platform-area or dominating-area displays and relatedweighing devices, systems, and methods. Additionally, the presentdisclosure relates to electronic body scales that use impedance-basedbiometric measurements. Various other aspects of the present disclosureare directed to biometrics measurements such as body composition andcardiovascular information. Impedance measurements can be made throughthe feet to measure fat percentage, muscle mass percentage and bodywater percentage. Additionally, foot impedance-based cardiovascularmeasurements can be made for an ECG and sensing the properties of bloodpulsations in the arteries, also known as impedance plethysmography(IPG), where both techniques can be used to quantify heart rate and/orpulse arrival timings (PAT). Cardiovascular IPG measures the change inimpedance through the corresponding arteries between the sensingelectrode pair segments synchronous to each heartbeat.

In certain embodiments, the present disclosure is directed toapparatuses and methods including a scale and external circuitry. Thescale includes a platform for a user to stand on, data-procurementcircuitry, processing circuitry, and an output circuit. Thedata-procurement circuitry includes force sensor circuitry and aplurality of electrodes integrated with the platform and configured forengaging the user with electrical signals and collecting signalsindicative of the user's identity and cardio-physiological measurementswhile the user is standing on the platform, processing circuitry, and anoutput circuit. The processing circuitry includes a CPU and a memorycircuit with user-corresponding data stored in the memory circuit. Theprocessing circuitry is arranged with (e.g., electrically integratedwith or otherwise in communication) the force sensor circuitry and theplurality of electrodes and configured and arranged to process dataobtained by the data-procurement circuitry while the user is standing onthe platform and therefrom generate cardio-related physiologic datacorresponding to the collected signals. The output circuit receives theuser data and, in response, sends the user data, including the dataindicative of the user's identity and the generated cardio-relatedphysiologic data, from the scale for reception at a remote location. Theoutput circuit further displays the user's weight and data indicative ofthe user's identity and/or the generated cardio-related physiologic datacorresponding to the collected signals using a user interface, which isinternal or external to the scale. The external circuitry is configuredand arranged to receive and validate the user data as concerning aspecific user associated with a user ID and determine physiologicparameters of the user using the user data.

A number of embodiments include methods for remotely determiningphysiologic parameters. For example, the method includes engaging auser, via a scale, with electrical signals and, therefrom, collectingsignals indicative of the user's identity while the user is standing ona platform of the scale. The scale includes a user display to displaydata to a user while the user is standing on the scale and the platformfor a user to stand on. Further, the scale includes data-procurementcircuitry, processing circuitry, and output circuitry. Thedata-procurement circuitry includes force sensor circuitry and aplurality of electrodes integrated with the platform. The processingcircuitry includes a CPU and a memory circuit with user-correspondingdata stored in the memory circuit. The processing circuitry isconfigured and arranged within the scale and under the platform uponwhich the user stands, and is electrically integrated with the forcesensor circuitry and the plurality of electrodes. The method furtherincludes processing, using the processing circuitry, data obtained bythe data-procurement circuitry while the user is standing on theplatform and therefrom generating cardio-related physiologic datacorresponding to the collected signals and displaying the user's weighton the user display. User data is output, using the output circuit, fromthe scale for reception by external circuitry at a remote location. Theuser data includes the data indicative of the user's identity and thegenerated cardio-related physiologic data. The method further includesvalidating the user data as concerning a specific user associated with auser ID, and determining, using the external circuitry, at least onephysiologic parameter of the user using the user data.

In another specific embodiment, a method includes receiving, at externalcircuitry, user data corresponding to a plurality of users from aplurality of scales, the user data including cardio-physiologicalmeasurements. Each scale includes a user display to display data to auser while the user is standing on the scale, a platform for a user tostand on, data-procurement circuitry, processing circuitry, and anoutput circuit. The data-procurement circuitry includes force-sensorcircuitry and a plurality of electrodes integrated with the platformconfigured and arranged for engaging the user with electrical signalsand collecting signals indicative of the user's identity andcardio-physiological measurements while the user is standing on theplatform. The processing circuitry is arranged with the plurality ofelectrodes to receive the collected signals obtained by thedata-procurement circuitry and, in response, derive and output the userdata to the external circuitry for assessment at a remote location thatis not integrated within the scale. The method includes receiving andvalidating the user data as concerning a respectively plurality of usersassociated with user IDs. The method includes identifying the respectiveplurality of users based on the user data received from the plurality ofscales, correlating the user data with respective user profiles based onthe identification of the respective plurality of users, determining,using the external circuitry, at least one physiologic parameter of eachrespective plurality of users using the respective user data. Thephysiologic parameter includes parameters selected from the groupconsisting of: pulse wave velocity, cardiac output, pre-ejection period,stroke volume, and a combination thereof.

In another embodiments, an apparatus comprises a plurality of scales andexternal circuitry. Each scale includes a user display to display datato a user while the user is standing on the scale, a platform for a userto stand on, data-procurement circuitry, and processing circuitry. Thedata-procurement circuitry includes force-sensor circuitry and aplurality of electrodes integrated with the platform configured andarranged for engaging the user with electrical signals and collectingsignals indicative of the user's identity and cardio-physiologicalmeasurements while the user is standing on the platform. The processingcircuitry is arranged with the plurality of electrodes to receive thecollected signals obtained by the data-procurement circuitry and, inresponse, derive and output the user data to the external circuitry forassessment at a remote location that is not integrated within the scale.The external circuitry receives the user data corresponding to aplurality of users from the plurality of scales, the user data includingcardio-physiological measurements and data indicative of the user'sidentity. Further, the external circuitry validates the user-data asconcerning the respective plurality of users based on the user datareceived from the plurality of scales and determines, using the externalcircuitry, at least one physiologic parameter of each respective userusing the respective user data.

In certain embodiments, aspects of the present disclosure areimplemented in accordance with and/or in combination with aspects of theunderlying PCT Application (Ser. No. PCT/US2016/062484), entitled“Scale-Based Parameter Acquisition Methods and Apparatuses”, filed onNov. 17, 2016, PCT Application (Ser. No. PCT/US2016/062505), entitled“Remote Physiologic Parameter Assessment Methods and PlatformApparatuses”, filed on Nov. 17, 2016, U.S. Provisional Application (Ser.No. 62/258,253), entitled “Initialization Method and Devices and UserPhysiological Platforms”, filed Nov. 20, 2015, U.S. ProvisionalApplication (Ser. No 62/260,174), entitled “Remote PhysiologicalParameter Determination Methods and Platform Apparatuses”, filed Nov.25, 2015, and U.S. Provisional Application (Ser. No. 62/266,523)entitled “Social Grouping Using a User-Specific Scale-Based EnterpriseSystem”, filed Dec. 11, 2015”, which are fully incorporated herein byreference.

The above discussion/summary is not intended to describe each embodimentor every implementation of the present disclosure. The figures anddetailed description that follow also exemplify various embodiments.

BRIEF DESCRIPTION OF THE DRAWINGS

Various example embodiments may be more completely understood inconsideration of the following detailed description in connection withthe accompanying drawings, in which:

FIG. 1a shows an apparatus consistent with aspects of the presentdisclosure;

FIG. 1b shows an example of remotely determining physiologic parametersusing an apparatus consistent with aspects of the present disclosure;

FIG. 1c shows an example of a scale wireless communicating with externalcircuitry consistent with aspects of the present disclosure;

FIG. 1d shows an example of apparatus comprised of a plurality of scaleand external circuitry consistent with aspects of the presentdisclosure;

FIG. 1e shows current paths through the body for the IPG trigger pulseand Foot IPG, consistent with various aspects of the present disclosure;

FIG. 1f is a flow chart illustrating an example manner in which auser-specific physiologic meter/scale may be programmed to providefeatures consistent with aspects of the present disclosure;

FIG. 2a shows an example of the insensitivity to foot placement on scaleelectrodes with multiple excitation and sensing current paths,consistent with various aspects of the present disclosure;

FIGS. 2b-2c show examples of electrode configurations, consistent withvarious aspects of the disclosure;

FIGS. 3a-3b show example block diagrams depicting circuitry for sensingand measuring the cardiovascular time-varying IPG raw signals and stepsto obtain a filtered IPG waveform, consistent with various aspects ofthe present disclosure;

FIG. 3c depicts an example block diagram of circuitry for operating corecircuits and modules, including for example those of FIGS. 3a-3b , usedin various specific embodiments of the present disclosure;

FIG. 3d shows an exemplary block diagram depicting the circuitry forinterpreting signals received from electrodes.

FIG. 4 shows an example block diagram depicting signal processing stepsto obtain fiducial references from the individual Leg IPG “beats,” whichare subsequently used to obtain fiducials in the Foot IPG, consistentwith various aspects of the present disclosure;

FIG. 5 shows an example flowchart depicting signal processing to segmentindividual Foot IPG “beats” to produce an averaged IPG waveform ofimproved SNR, which is subsequently used to determine the fiducial ofthe averaged Foot IPG, consistent with various aspects of the presentdisclosure;

FIG. 6a shows examples of the Leg IPG signal with fiducials; thesegmented Leg IPG into beats; and the ensemble-averaged Leg IPG beatwith fiducials and calculated SNR, for an exemplary high-qualityrecording, consistent with various aspects of the present disclosure;

FIG. 6b shows examples of the Foot IPG signal with fiducials derivedfrom the Leg IPG fiducials; the segmented Foot IPG into beats; and theensemble-averaged Foot IPG beat with fiducials and calculated SNR, foran exemplary high-quality recording, consistent with various aspects ofthe present disclosure;

FIG. 7a shows examples of the Leg IPG signal with fiducials; thesegmented Leg IPG into beats; and the ensemble averaged Leg IPG beatwith fiducials and calculated SNR, for an exemplary low-qualityrecording, consistent with various aspects of the present disclosure;

FIG. 7b shows examples of the Foot IPG signal with fiducials derivedfrom the Leg IPG fiducials; the segmented Foot IPG into beats; and theensemble-averaged Foot IPG beat with fiducials and calculated SNR, foran exemplary low-quality recording, consistent with various aspects ofthe present disclosure;

FIG. 8 shows an example correlation plot for the reliability inobtaining the low SNR Foot IPG pulse for a 30-second recording, usingthe first impedance signal as the trigger pulse, from a study including61 test subjects with various heart rates, consistent with variousaspects of the present disclosure;

FIGS. 9a-b show an example configuration to obtain the pulse transittime (PTT), using the first IPG as the triggering pulse for the Foot IPGand ballistocardiogram (BCG), consistent with various aspects of thepresent disclosure;

FIG. 10 shows nomenclature and relationships of various cardiovasculartimings, consistent with various aspects of the present disclosure;

FIG. 11 shows an example graph of PTT correlations for two detectionmethods (white dots) Foot IPG only, and (black dots) Dual-IPG method,consistent with various aspects of the present disclosure;

FIG. 12 shows an example graph of pulse wave velocity (PWV) obtainedfrom the present disclosure compared to the ages of 61 human testsubjects, consistent with various aspects of the present disclosure;

FIG. 13 shows another example of a scale with interleaved footelectrodes to inject and sense current from one foot to another foot,and within one foot, consistent with various aspects of the presentdisclosure;

FIG. 14a shows another example of a scale with interleaved footelectrodes to inject and sense current from one foot to another foot,and measure Foot IPG signals in both feet, consistent with variousaspects of the present disclosure;

FIG. 14b shows another example of a scale with interleaved footelectrodes to inject and sense current from one foot to another foot,and measure Foot IPG signals in both feet, consistent with variousaspects of the present disclosure;

FIG. 14c shows another example approach to floating current sources isthe use of transformer-coupled current sources, consistent with variousaspects of the present disclosure;

FIGS. 15a-d show an example breakdown of a scale with interleaved footelectrodes to inject and sense current from one foot to another foot,and within one foot, consistent with various aspects of the presentdisclosure;

FIG. 16 shows an example block diagram of circuit-based building blocks,consistent with various aspects of the present disclosure;

FIG. 17 shows an example flow diagram, consistent with various aspectsof the present disclosure;

FIG. 18a shows an example scale communicatively coupled to a wirelessdevice, consistent with various aspects of the present disclosure;

FIG. 18b shows an example scale communicatively coupled to externalcircuitry and various data types provided to a user, consistent withvarious aspects of the present disclosure; and

FIGS. 19a-c show example impedance as measured through different partsof the foot based on the foot position, consistent with various aspectsof the present disclosure.

While various embodiments discussed herein are amenable to modificationsand alternative forms, aspects thereof have been shown by way of examplein the drawings and will be described in detail. It should beunderstood, however, that the intention is not to limit the disclosureto the particular embodiments described. On the contrary, the intentionis to cover all modifications, equivalents, and alternatives fallingwithin the scope of the disclosure including aspects defined in theclaims. In addition, the term “example” as used throughout thisapplication is only by way of illustration, and not limitation.

DETAILED DESCRIPTION

Aspects of the present disclosure are believed to be applicable to avariety of different types of apparatuses, systems, and methodsinvolving remotely determining physiologic parameters of a user usinguser data obtained by a scale. In certain implementations, aspects ofthe present disclosure have been shown to be beneficial when used in thecontext of a weighing scale with electrodes configured for engaging withthe user and generating cardio-related physiologic data, such as dataindicative of a BCG or ECG of a user. In some embodiments, the externalcircuitry determines the physiologic parameters, which can includeclinical indicators that may not be displayed to the user. The externalcircuitry controls access to information by not allowing access to theclinical indicators to the user, without a prescription from aphysician, while still allowing access to other data such as bodyweight,body mass index, heart rate, body fat percentage, and cardiovascularage. These and other aspects can be implemented to address challenged,including those discussed in the background above. While not necessarilyso limited, various aspects may be appreciated through a discussion ofexamples using such exemplary contexts.

Accordingly, in the following description various specific details areset forth to describe specific examples presented herein. It should beapparent to one skilled in the art, however, that one or more otherexamples and/or variations of these examples may be practiced withoutall the specific details given below. In other instances, well knownfeatures have not been described in detail so as not to obscure thedescription of the examples herein. For ease of illustration, the samereference numerals may be used in different diagrams to refer to thesame elements or additional instances of the same element. Also,although aspects and features may in some cases be described inindividual figures, it will be appreciated that features from one figureor embodiment can be combined with features of another figure orembodiment even though the combination is not explicitly shown orexplicitly described as a combination.

In accordance with a number of embodiments, physiologic parameter datais collected using an apparatus, such as a weighing scale or otherplatform that the user stands on. The user (e.g., co-workers, friends,roommates, colleagues), may use the apparatus in the home, office,doctors office, or other such venue on a regular and frequent basis, thepresent disclosure is directed to a substantially-enclosed apparatus, aswould be a weighing scale, wherein the apparatus includes a platformwhich is part of a housing or enclosure and a user display to outputuser-specific information for the user while the user is standing on theplatform. The platform includes a surface area with electrodes that areintegrated and configured and arranged for engaging a user as he or shesteps onto the platform. Within the housing is processing circuitry thatincludes a CPU (e.g., one or more computer processor circuits) and amemory circuit with user-corresponding data stored in the memorycircuit. The platform, over which the electrodes are integrated, isintegrated and communicatively connected with the processing circuitry.The processing circuitry is programmed with modules as a set ofintegrated circuitry which is configured and arranged for automaticallyobtaining a plurality of measurement signals (e.g., signals indicativeof cardio-physiological measurements) from the plurality of electrodes.The processing circuitry generates, from the signals, cardio-relatedphysiologic data manifested as user data.

The user data, in various embodiments, is processed to determinephysiologic parameters of the user and other data, such ascardio-physiological data and wellness data. The physiologic parameters,in various embodiments, includes information that is regulated by agovernment agency, such as the Food and Drug Administration (FDA),and/or otherwise requires a prescription from a physician for the userto obtain. The other data, such as the cardio-physiological data andwellness data, by contrast, includes derived measurements that are“non-regulated” by agencies, such as the FDA. To obtain suchinformation, a user may purchase a scale and use the scale over thecounter and without a physician's prescription. The scale, if the userdata is further processed, can provide the additional prescription (Rx)health information to the user, via the physiologic parameters, that maybe beneficial for the user or the user's physician to access. However,the user may be unable to access the information without a prescriptionfrom a physician and/or could not purchase the scale in the first placewithout a prescription if the scale was enabled to provide the Rx healthinformation. Embodiments in accordance with the present disclosureinclude processing the user data on external circuitry to determinephysiologic parameters, which can include Rx health information. Invarious embodiments, the external circuitry controls access to the Rxhealth information by allowing a physician to access to the informationbut not a user. The user is provided access to non-regulated data, suchas other additional health information, and granted access to the Rxhealth information in response to a prescription from the physician.Furthermore, the Rx health information is used to update a user profile,such as a user health profile at the physician's office.

In accordance with various embodiments, the external circuitry receivesuser data from a plurality of scales. Each scale provides data for oneor more different users and/or can be located at different locations.The external circuitry identifies the users corresponding to thereceived user data, validates the user data as concerning the identifiedusers, and correlates the user data with profiles based onidentification of the respective plurality of users. The externalcircuitry provides physiologic parameters, such as diagnosis,conditions, and/or treatments, PWV, cardiac output, pre-ejection periodand stroke volume by processing the data from the scales. In somespecific aspects, the external circuitry controls access to the profilesby allowing access to physiologic parameters and other data to aphysician and not allowing access to the physiologic parameters to theusers. In various embodiments, the external circuitry allows access toother data to the user, without a prescription. For example, theexternal circuitry allows access by granting access to the respectiveprofile or portions of the data in the profile and/or by sending therespective data to the scale (or another user device) for display.Example data that is non-regulated by an agency and can be provided tothe user without a prescription includes bodyweight, body mass index,heart rate, body-fat percentage, and cardiovascular age. By controllingaccess to the physiologic parameters, that includes Rx healthinformation, the scale provides the advanced functions of determiningthe clinical indications while being sold over-the-counter and the usercan access this data through their physician. The physiologic parameterscan be used by the physician for further analysis and/or to providehealth advice and/or diagnosis, such as medications.

In accordance with various embodiments, the user data is based onsensing, detection, and quantification of at least two simultaneouslyacquired impedance-based signals. The simultaneously acquiredimpedance-based signals are associated with quasi-periodicelectro-mechanical cardiovascular functions, and simultaneouscardiovascular signals measured by the impedance sensors, due to thebeating of an individual's heart, where the measured signals are used todetermine at least one cardiovascular related characteristic of the userfor determining the heart activity, health, or abnormality associatedwith the user's cardiovascular system. The sensors can be embedded in auser platform, such as a weighing scale-based platform, where the userstands stationary on the platform, with the user's feet in contact withthe platform, where the impedance measurements are obtained where theuser is standing with bare feet.

In certain embodiments, the plurality of impedance-measurement signalsincludes at least two impedance-measurement signals between the one footand the other location. Further, in certain embodiments, a signal isobtained, based on the timing reference, which is indicative ofsynchronous information and that corresponds to information in a BCG.Additionally, the methods can include conveying modulated currentbetween selected ones of the electrodes. The plurality ofimpedance-measurement signals may, for example, be carried out inresponse to current conveyed between selected ones of the electrodes.Additionally, the methods, consistent with various aspects of thepresent disclosure, include a step of providing an IPG measurementwithin the one foot. Additionally, in certain embodiments, the twoelectrodes contacting one foot of the user are configured in aninter-digitated pattern of positions over a base unit that containscircuitry communicatively coupled to the inter-digitated pattern. Thecircuitry uses the inter-digitated pattern of positions for the step ofdetermining a plurality of pulse characteristic signals based on theplurality of impedance-measurement signals, and for providing an IPGmeasurement within the one foot. As discussed further herein, andfurther described in U.S. patent application Ser. No. 14/338,266 filedon Oct. 7, 2015, which is herein fully incorporated by reference for itsspecific teaching of inter-digitated pattern and general teaching ofsensor circuitry, the circuitry can obtain the physiological data in anumber of manners.

In medical (and security) applications, for example, the impedancemeasurements obtained from the plurality of integrated electrodes canthen be used to provide various cardio-related information that isuser-specific including, as non-limiting examples, synchronousinformation obtained from the user and that corresponds to informationin a ballistocardiogram (BCG) and an impedance plethysmography (IPG)measurements. By ensuring that the user, for whom such data wasobtained, matches other bio-metric data as obtained concurrently for thesame user, medical (and security) personnel can then assess, diagnoseand/or identify with high degrees of confidence and accuracy.

In various related aspects, the scale and external circuitry providevarious additional health information to the user in response varioususer inputs and/or the user data. The additional health information, invarious embodiments, includes tables, information, and/or correlates tothe cardio-related information that is determined using the externalcircuitry (e.g., physiologic parameters) and is non-RX healthinformation. In various embodiments, the cardio-related information mayindicate the user has and/or is at risk for a disorder, disease, and/orhas a particular symptom. The additional health information is providedto the user that includes generic information for the disorder, disease,and/or particular symptom without specific information about the userand/or an indication that the user has and/or is at risk for thedisorder, disease, and/or symptom. In a number of embodiments, thegeneric information is based on and/or correlated to specific userinputs, such as a category of interest (e.g., demographic of interest,disorder/disease of interest), among other inputs. For example, while,after and/or before taking the various impedance measurements, the useris asked a number of questions. The scale can display the questions, askthe questions using a natural language interface (e.g., a speakercomponent of the device asks the user questions using computer generatedsounds). In some embodiments, the scale instructs another usercircuitry, such as a user device (e.g., cell phone, tablet, computingdevice, smart watch) to ask the questions, and in response to the user'sinput, the user device provides the responses to the scale and/or theexternal circuitry. Based on the inputs, categories of interest for theuser are determined and used to generate the additional healthinformation.

As used herein, a user device includes processing circuitry and outputcircuitry to collect various data (e.g., signals) and communicate thedata to the scale and/or other circuitry. Example user devices includecellphones, tablets, standalone server, among other devices. The userdevice can be a wearable device that is worn by a user, such as on auser's wrist, head, or chest. Example wearable devices includesmartwatches and fitness bands, smart glasses, chest heart monitors,etc. In other aspects, the user device further includes sensor circuitryor other circuit to collect physiologic data from the user, and, canoptionally be in secured communication with the scale or othercircuitry. For example, the user device includes smartwatches or fitnessbands that collect heart rate and/or ECG and/or body temperature,medical devices, implanted medical devices, smart beds, among otherdevices. Example physiologic data collected by user devices includesglucose measurements, blood pressure, ECG or other cardio-related data,body temperature, among other data. The terms “user device” and“wearable device”, can be interchangeably used.

In a number of a specific embodiments, the user stands on the scale. Thescale collects signals using the data-procurement circuitry, and sendsat least a portions of the signals to the external circuitry. Theexternal circuitry processes the collected signals, sent as user data,and determines cardio-related information, which may include Rxinformation. During the processing by the external circuitry, the scale(and/or a user device) asks the user if the user is interested inreceiving various health information and/or would like a table providedthat is based on various demographics, disorders, and/or othercategories of interest. In response to the user providing an inputindicating they are interested, the scale asks the user to inputcategories of interest (demographics, disorders, symptoms, etc.). Insome embodiments, the scale provides the inputs to the externalcircuitry and the external circuitry derives additional healthinformation using the inputs and the user data. For example, theexternal circuitry can determine health information that is based on thedemographics the user provides (e.g., particular sex, age, ethnicity)and various values and/or symptoms of a disorder/disease/symptomcorrelated to the cardio-related information of the user. As aparticular specific example, the user can provide that they areinterested in a table for males, 45-55, and African-American. The userdata may indicate that the user has and/or is at risk for atrialfibrillation. In various embodiments, the external circuitry generates atable which includes general risk factors and/or symptoms for variousheart-related conditions, which includes atrial fibrillation, forAfrican-American males ages 45-55. The information provided does notinclude particular values for the user and/or any indication that theuser has atrial fibrillation. In this manner, the scale does not provideRx health information without a prescription from a physician and can beprovided over-the-counter.

Turning now to the figures, FIG. 1a shows an apparatus consistent withaspects of the present disclosure. The apparatus includes a platform 101and a user display 102. The user, as illustrated by FIG. 1a is standingon the platform 101 of the apparatus. The user display 102 is arrangedwith the platform 101. As illustrated by the dotted lines of FIG. 1a ,the apparatus further includes processing circuitry 104,data-procurement circuitry 138, and physiologic sensors 108. That is,the dotted lines illustrate a closer view of components of theapparatus.

The physiologic sensors 108, in various embodiments, include a pluralityof electrodes integrated with the platform 101. The electrodes andcorresponding force-sensor circuitry 139 are configured to engage theuser with electrical signals and to collect signals indicative of theuser's identity and cardio-physiological measurements while the user isstanding on the platform 101. For example, the signals are indicative ofphysiologic parameters of the user and/or are indicative of or includephysiologic data, such as data indicative of a BCG or ECG and/or actualbody weight or heart rate data, among other data. Although theembodiment of FIG. 1a illustrates the force sensor circuitry 139 asseparate from the physiological sensors 108, one of skill in the art mayappreciate that the force sensor circuitry 139 are physiologicalsensors. The user display 102 is arranged with the platform 101 and theelectrodes to output user-specific information for the user while theuser is standing on the platform 101. The processing circuitry 104includes CPU and a memory circuit with user-corresponding data 103stored in the memory circuit. The processing circuitry 104 is arrangedunder the platform 101 upon which the user stands, and is electricallyintegrated with the force-sensor circuitry 139 and the plurality ofelectrodes (e.g., the physiologic sensors 108). The data indicative ofthe identity of the user includes, in various embodiments,user-corresponding data, biometric data obtained using the electrodesand/or force sensor circuitry, voice recognition data, images of theuser, input from a user's device, and/or a combination thereof and asdiscussed in further detail herein. For example, the scale can capturevoice sounds from the user speaking, and the user data indicative of theidentity includes the voice sounds captured.

The user-corresponding data includes information about the user that mayor may not be obtained using the physiologic sensors 108, such asdemographic information or historical information. Exampleuser-corresponding data includes height, gender, age, ethnicity,exercise habits, eating habits, cholesterol levels, previous healthconditions or treatments, family medical history, and/or a historicalrecord of variations in one or more of the listed data. Theuser-corresponding data can be obtained directly from the user (e.g.,the user inputs to the scale) and/or from another circuit (e.g., a smartdevice, such a cellular telephone, smart watch and/or fitness device,cloud system, etc.).

In various embodiments, the processing circuitry 104 is electricallyintegrated with the force-sensor circuitry 139 and the plurality ofelectrodes and configured to process data obtained by thedata-procurement circuitry 138 while the user is standing on theplatform 101. The processing circuitry 104, for example, generatescardio-related physiologic data corresponding to the collected signalsand that is manifested as user data. Further, the processing circuitry104 generates data indicative of the identity of the user, such as auser ID and/or other user identification metadata. The user ID can be,for example, in response to confirming identification of the user usingthe collected signals indicative of the user's identity.

The user data, in some embodiments, includes the raw signals,bodyweight, body mass index, heart rate, body-fat percentage,cardiovascular age, among other data. In various embodiments, theprocessing circuitry 104, with the user display 102, displays at least aportion of the user data to the user. For example, user data that isnot-regulated is displayed to the user, such as user weight.Alternatively and/or in addition, the user data is stored. For example,the user data is stored on the memory circuit of the processingcircuitry (e.g., such as the physiologic data stored on thephysiological user data database 107 illustrated by FIG. 1a ). Theprocessing circuitry 104, in various embodiments, correlates thecollected user data (e.g., physiologic user-data) withuser-corresponding data, such as storing identification metadata thatidentifies the user with the respective data. An algorithm to determinethe physiologic data from raw signals can be located on the scale, onanother device (e.g., external circuitry, cellphone), and on a Cloudsystem. For example, the Cloud system can learn to optimize thedetermination and program the scale to subsequently perform thedetermination locally. The Cloud system can perform the optimization andprogramming for each user of the scale.

In some embodiments, the scale collects physiologic data from otherdevices, such as medical devices, user devices, wearable devices, and/orremote-physiological devices. The data can include glucose measurements,blood pressure, ECG or other cardio-related data, body temperature,among other physiologic data. Further, the scale can act as a hub tocollect data from a variety of sources. The sources includes theabove-noted user devices. The scale can incorporate a web server (URL)that allows secure, remote access to the collected data. For example,the secure access can be used to provide further analysis and/orservices to the user.

In a number of embodiments, the processing circuitry 104 and/or thescale include an output circuit 106. The output circuit 106 receives theuser data and, in response, sends the user data, including the dataindicative of the user's identity and the generated cardio-relatedphysiologic data, from the scale for reception at a remote location(e.g., to external circuitry 111 for assessment). In variousembodiments, the output circuit 106. In various embodiments, the outputcircuit 106 provides data to user via a user interface. The userinterface can be integrated with the platform 101 (e.g., internal to thescale) and/or can be integrated with external circuitry that is notlocated under the platform 101. In some embodiments, the user interfaceis a plurality of user interfaces, in which at least one user interfaceis integrated with the platform 101 and at least one user interface isnot integrated with the platform 101.

A user interface includes or refers to interactive components of adevice (e.g., the scale) and circuitry configured to allow interactionof a user with the scale (e.g., hardware input/output components, suchas a screen, speaker components, keyboard, touchscreen, etc., andcircuitry to process the inputs). A user display includes an outputsurface (e.g., screen) that shows text and/or graphical images as anoutput from a device to a user (e.g., cathode ray tube, liquid crystaldisplay, light-emitting diode, organic light-emitting diode, gas plasma,touch screens, etc.) For example, output circuit can provide data fordisplay on the user display 102 the user's weight and the dataindicative of the user's identity and/or the generated cardio-relatedphysiologic data corresponding the collected signals. The externalcircuitry 111 is at a remote location from the scale and is notintegrated with the scale. The communication, in various embodiments,includes a wireless communication and/or utilizes a cloud system.

The user interface is or includes a graphical user interface (GUI), afoot-controlled user interface (FUI), and/or voice input/outputcircuitry. The user interface can be integrated with the platform 101(e.g., internal to the scale) and/or can be integrated with externalcircuitry that is not located under the platform 101. In someembodiments, the user interface is a plurality of user interfaces, inwhich at least one user interface is integrated with the platform 101and at least one user interface is not integrated with the platform 101.Example user interfaces include input/output devices, such as displayscreens, touch screens, microphones, etc.

A FUI is a user interface that allows for the user to interact with thescale via inputs using their foot and/or via graphic icons or visualindicators near the user's foot while standing on the platform. Inspecific aspects, the FUI receives inputs from the user's foot (e.g.,via the platform) to allow the user to interact with the scale. The userinteraction includes the user moving their foot relative to the FUI, theuser contacting a specific portion of the user display, etc.

A GUI is a user interface that allows the user to interact with thescale through graphical icons and visual indicators. As an example, theexternal circuitry includes a GUI, processing circuitry, and outputcircuitry to communicate with the processing circuitry of the scale. Thecommunication can include a wireless or wired communication. Exampleexternal circuitry can include a wired or wireless tablet, a cellphone(e.g., with an application), a smartwatch or fitness band, smartglasses,a laptop computer, among other devices. In other examples, the scaleincludes a GUI and voice input/output circuitry (as further describedbelow) integrated in the platform 101. The user interact with the scalevia graphical icons and visual indicators provided via the GUI and voicecommands from the user to the scale.

Voice input/output circuitry (also sometimes referred to as speechinput/output) can include a speaker, a microphone, processing circuitry,and other optional circuitry. The speaker outputs computer-generatedspeech (e.g., synthetic speech, instructions, messages) and/or othersounds (e.g., alerts, noise, recordings, etc.) The computer-generatedspeech can be predetermined, such as recorded messages, and/or can bebased on a text-to-speech synthesis that generates speech from computerdata. The microphone captures audio, such a voice commands from the userand produces a computer-readable signal from the audio. For example, thevoice input/output circuitry can include an analog-to-digital converter(ADC) that translates the analog waves captured by the microphone (fromvoice sounds) to digital data. The digital data can be filtered usingfilter circuitry to remove unwanted noise and/or normalize the capturedaudio. The processing circuitry (which can include or be a component ofthe processing circuitry 104) translates the digital data to computercommands using various speech recognition techniques (e.g., patternmatching, pattern and feature matching, language modeling andstatistical analysis, and artificial neural networks, among othertechniques).

The external circuitry 111 receives the user-data, validates the userdata as concerning a specific user associated with a user ID, anddetermines at least one physiologic parameter of the user using the userdata. As discussed in further detail herein, the validation can be basedon the data indicative of the user's identity. For example, the dataindicative of the user's identity can be the user ID and/or can beassociated with the user ID (e.g., is mapped to and/or otherwisecorrelated to). The external circuitry 111, in some embodiments,communicates the determined physiologic parameter back to the scaleand/or another user device for display to the user. Alternatively and/orin addition, the external circuitry controls access to the physiologicparameter, as discussed further herein.

The physiologic parameter, in various embodiments, includes PWV, BCG,cardiac output, pre-ejection period, stroke volume, arterial stiffness,respiration, and/or other Rx health information. The user data, in someembodiments, includes the raw force signals, bodyweight, heartrate,balance, tremors, body mass index and/or percentage, among othernon-regulated physiologic data.

Although the present examples embodiments provided above are inreference to external circuitry performing the determination,embodiments in accordance with the present disclosure are not solimited. For example, the processing circuitry 104 can determine thephysiologic parameter while the user is standing on the platform 101.

In accordance with various embodiments, although not illustrated by FIG.1a , the apparatus includes an additional sensor circuitry that isexternal to the scale. The additional sensor circuitry can include acommunication circuit and is configured and arranged to engage the userwith electrical signals and collect therefrom signals indicative of anECG of the user. The sensor circuitry, which may include and/or becorrelated with processing circuitry configured to derive an ECG fromthe collected signals. The sensor circuitry communicates the ECG to theexternal circuitry 111 and the scale can communicate a BCG to theexternal circuitry 111.

FIG. 1b shows an example of remotely determining physiologic parametersusing an apparatus consistent with aspects of the present disclosure.The apparatus illustrated by FIG. 1b can include the apparatus,including the platform 101 and user display 102, as previouslyillustrated and discussed with regard to FIG. 1a . As illustrated, theapparatus includes a platform, a user display configured and arrangedwith the platform and the plurality of electrodes to outputuser-specific information for the user while the user is standing on theplatform, data-procurement circuitry 138, and processing circuitry 104.The data-procurement circuitry 138 includes force-sensor circuitry and aplurality of electrodes (e.g., the physiologic sensors 108) which areintegrated with the data-procurement circuitry 138. The processingcircuitry 104 includes a CPU and a memory circuit withuser-corresponding data stored in the memory circuit. As previouslydiscussed, the scale includes an output circuit to send the user data toexternal circuitry 111. The external circuitry 111 can receive theuser-data and determine the physiologic parameters of the user using theuser data.

For example, as illustrated by FIG. 1b , the scale at block 116 waitsfor a user to stand on the platform. User-corresponding data 103 isinput and/or received prior to the user standing on the scale and/or inresponse to. In various embodiments, in response to the user standing onand/or approaching the scale, the apparatus obtains identification datato identify the user. Example identification data, as discuss furtherherein with regard to FIG. 2a , includes the time of day, length offoot, spoken words from the user, weight, height, facial features, etc.At block 117, the apparatus, using the processing circuitry 104,confirms identification of the user when the user is standing on theplatform and/or as the user approaches the platform. The identification,in various embodiments, is based on the identification data and/or userdata. For example, the processing circuitry 104 compares theidentification data to stored user-corresponding data 103 to confirmidentification of the user. Further, in some embodiments, additionaluser-corresponding data is obtained in response to the user standing onand/or approaching the platform.

In response to the user standing on the scale, the scale collectssignals indicative of cardio-physiological measurements (e.g., forcesignals). The processing circuitry 104, at block 118, processes thesignals to generate cardio-related physiologic data manifested as userdata and outputs the user data to the external circuitry 111. In variousembodiments, the processing includes adding (and later storing) datawith a time stamp indicating a time at about when the physiologicparameter data is obtained.

The external circuitry 111, at block 119, receives the user data,validates the user data as corresponding to the user using the user ID,and determines at least one physiologic parameter using the user-data.Example physiologic parameters includes PWV, BCG, respiration, arterialstiffness, cardiac output, pre-ejection period, stroke volume, and acombination thereof. The external circuitry 111 then outputs thephysiologic parameter. The output can be to the scale for display, suchas illustrated at block 121 and/or to a memory circuit corresponding tothe external circuitry 111 (e.g., as illustrated with regard to FIG.1c-1e ). The scale, in various embodiments, updates the storeduser-corresponding data 103 and/physiologic user data 107 of the user asstored on the memory circuit of the processing circuitry 104 of thescale.

In accordance with a number of embodiments, the scale including theprocessing circuitry provides a number of questions to the user. Thequestions can be provided via a speaker component of the scaleoutputting computer generated natural voice (via a natural languageinterface), displaying the questions on the user display 102, and/oroutputting the questions to another user-device. In various embodiments,the questions include asking the user if the user is interested inadditional health information and if the user has particular categoriesof interest. In various embodiments, the categories of interest includea set of demographics, disorders, diseases, and/or symptom that the useris interested, and/or other topics. The scale provides the input to theexternal circuitry 111 and the external circuitry 111 derives theadditional health information for the user. The additional healthinformation can include a table that corresponds to the categories ofinterest and/or corresponds to the physiologic parameter and/or clinicalindications determined without providing any specific values and/orindication related to the physiologic parameter. The user is providedthe additional health information by the external circuitry 111outputting the information to the scale and/or another user-device, andthe scale and/or other user-device displays the information. In variousembodiments, the information can be printed by the user to bring to aphysician. In various related-aspects, the scale using the processingcircuitry 104 generates the additional health information instead of theexternal circuitry 111. As previously described, the scale can(alternatively and/or in addition to a FUI or GUI) have a voiceinput/output circuitry that can obtain be used obtain the categories ofinterest from the user via voice comments and inputs user information inresponse (e.g., a speaker component to capture voice sounds from theuser and processing circuitry to recognize the voice commands and/orspeech).

The additional health information is generated, in various embodiments,by comparing and/or correlating the categories of interest to raw dataobtained by the data-procurement circuitry 138. In various embodiments,the correlation/comparison include comparing statistical data of asample census pertinent to the categories of interest and the at leastone physiologic parameter. The statistical data of a sample censusincludes data of other users that are correlated to the categories ofinterest. In such instances, the additional health information caninclude a comparison of data measured while the user is standing on theplatform to sample census data (e.g., may contain Rx information). Inother related embodiments, the correlation/comparison includes comparingstatistical data of a sample census pertinent to the categories ofinterest and values of the least one physiologic parameter of the samplecensus. In such instances, the additional health information includesaverage physiologic parameter values of the sample census that is set bythe user, via the categories of interest, and may not include actualvalues corresponding to the user (e.g., does not contain Rxinformation).

For example, if the categories of interest are demographic categories,the additional health information can include various physiologicparameter values of average users in the demographic categories and/orvalues of average users with a clinical indication that correlates to aphysiologic parameter of the user. Alternatively and/or in addition, theadditional health information can include general medical insightsrelated to the categories of interest. For example, “Did you know if youare over the age of 55 and have gained 15 pounds, you are at risk for aparticular disease/disorder?” The scale can ask the user if the userwould like to include this factor or disease in their categories ofinterest to dynamically update the categories of interest of the user.

Various categories of interest, in accordance with the presentdisclosure, include demographics of the user, disorders, diseases,symptoms, prescription or non-prescription drugs, treatments, pastmedical history, family medical history, genetics, life style (e.g.,exercise habits, eating habits, work environment), among othercategories and combinations thereof. In a number of embodiments, variousphysiological factors can be an indicator for a disease and/or disorder.For example, an increase in weight, along with other factors, canindicate an increased risk of atrial fibrillation. Further, atrialfibrillation is more common in men. However, symptoms of variousdisorders or disease can be different depending on categories ofinterest (e.g., atrial fibrillation symptoms can be different betweenmen and women). For example, in women, systolic blood pressure isassociated with atrial fibrillation. In other instances, sleep apnea maybe assessed via an ECG and can be correlated to weight of the user.Furthermore, various cardiac conditions can be assessed using an ECG.For example, atrial fibrillation (AFIB) can be characterized and/oridentified in response to a user having indistinguishable orfibrillating p-waves, and indistinguishable baseline/inconsistent beatfluctuations. Atrial flutter, by contrast, can be characterized byhaving indistinguishable p-wave, variable heart rate, having QRScomplexes, and a generally regular rhythm. Ventricular tachycardia (VT)can be characterized by a rate of greater than 120 beats per minute, andshort or broad QRS complexes (depending on the type of VT).Atrio-Ventricular (AV) block can be characterized by PR intervals thatare greater than normal (e.g., a normal range for an adult is generally0.12 to 0.20 seconds), normal-waves, QRS complexes can be normal orprolong shaped, and the pulse can be regular (but slow at 20-40 beatsper minute). For more specific and general information regarding atrialfibrillation and sleep apnea, reference is made herein tohttps://www.clevelandclinicmeded.com/medicalpubs/diseasemanagement/cardiology/atrial-fibrillation/andhttp://circ.ahajournals.org/content/118/10/1080.full, which are fullyincorporated herein for their specific and general teachings. Further,other data and demographics that are known and/or are developed can beadded and used to derive additional health information.

For example, the categories of interest for a particular user caninclude a change in weight, age 45-55, and female. The scale obtains rawdata using the data-procurement circuitry 138 and the categories ofinterest from the user. The scale outputs the raw data and categories ofinterest to the external circuitry 111 and the external circuitry 111correlates the categories of interest to the raw data and derivesadditional health information therefrom. Further, the external circuitry111, over time, historically collects and correlates the categories ofinterest of the user and data from the data-procurement circuitry. Theexternal circuitry 111, in various embodiments, sends the data to aphysician and/or additional health information to the user (to printand/or otherwise view).

In various embodiments, the external circuitry controls access to theleast one physiologic parameter. For example, the external circuitry 111can allow access to the at least one physiologic parameter to aphysician corresponding with the user and/or not allow access to the atleast one physiologic parameter to the user. The user can be grantedaccess, for instance, in response to a prescription provided by thephysician. For example, the user data can be collected and determinedbut the user is not allowed access to the features, such as access tothe user data or service related to the user data until governmentclearance is obtained. For example, the scale collects and stores theuser data but does not display or otherwise allow the user access to theuser data until clearance is obtained for each feature, whichretrospectively enables the feature and/or service. Alternatively and/orin addition, the feature and/or service is not provided until a weightedvalue is received (e.g., payment).

In a number of embodiments, the external circuitry 111 determinesadditional physiologic parameters and/or data, such as further clinicalindications, of the user using the determined physiologic parameter. Forexample, the determined physiologic parameter can include an ECG and theexternal circuitry 111 can determine a BCG using the ECG. Alternativelyand/or in addition, the external circuitry 111 can determine a healthstatus of the user using the determined physiologic parameter, such as acondition or treatment.

The scale can be used by multiple different users. A subset or each ofthe different users can have data output to external circuitry and canreceive additional health data, related to different categories ofinterest. For example, each of a plurality of users have previously orcurrent entered different categories of interest. The scale can store anindication of the categories of interest and as associated with eachrespect user. The scale and/or external circuitry can selectively trackparticular data based on the different categories of interest andprovide the additional health data, which can be updated over time,responsive to recognizing a particular user.

The scale can be used in different settings and/or modes, such as aconsumer mode, a professional mode, and a combination mode. A consumermode includes a scale as used and/or operated in a consumer setting,such as a dwelling. As a specific example, a scale is located in adwelling with five different people. Each of the five different peopleuse the scale, and three of the five people have previously providedinputs to the scale that indicate different categories of interest.Prior to providing additional health information to a user, the identityof the respective user is verified via the scale using a scale-basedbiometric. Responsive to identifying the user, the scale identifies theparticular categories of interest corresponding to the user, outputs allor portions of the data to the external circuitry. The externalcircuitry generates the additional health information based on thecategories of interest and the user data, and outputs the same to thescale to provide to the user. As users in a consumer mode may befamiliar with one another (e.g., live together), the identification ofthe user by the scale can be based on weight, body-mass-index, and/orother data. Although embodiments are not so limited and theidentification can be based on other biometrics and/or passcodes.

In other instances, the scale is used in a professional setting, such asa medical office, and/or in a professional mode. A professional modeincludes an operation of the scale as used and/or operated in aprofessional setting, such as a doctor's office, exercise facility,nursing home, etc. In a professional mode, the scale is used bydifferent users that may not be familiar with one another. The differentusers may have services with the professional to track and/or aggregatedata from a peripheral device and/or to provide health information. Aperipheral device includes or refers to circuitry that is not integratedwithin the scale and can communicate with the scale via a wired orwireless connection. In some instances, a user can be providedadditional health information as service while waiting for theprofessional, such as while waiting to see a doctor. The scale receivesthe additional health information from the external circuitry and eitherdisplays the additional health information using a user interface of thescale and/or via direct communication (e.g., WiFi, Bluetooth, NFC) witha user device (e.g., cellphone, tablet) that is within a thresholddistance of the scale. Similar to the consumer mode, the scale canselectively provide the services by verifying the identity of the userusing a scale-based biometric. The identification can include ahigher-level biometric and/or identification than the consumer mode. Asa specific professional mode example, a scale is located at a doctor'soffice and is used to obtain data from multiple patients (e.g., 10 in aday, 500 in a year). When a patient checks-in, they stand on the scaleand the scale-obtained data is output to external circuitry for documentretention and/or other purposes. A subset (or all) of the patients haveactivated a service with doctor that corresponds with and/or includesproviding additional health information while the user is waiting and/orbased on categories of interest. For example, a user indicates aninterest in learning more about AFIB, which the scale outputs toexternal circuitry along with user data obtained by the scale. Theexternal circuitry generates additional health information correlatedwith AFIB and the user data. For example, the additional healthinformation includes various risks factors for AFIB and identifieslifestyle changes that can reduce the risk factors. The externalcircuitry communicates the additional health information to the scalevia an Internet (or direct communication) connection and the scaleoutputs the additional health information to a cellphone of the user viaan NFC or Bluetooth communication. The scale, in the professional mode,may be used to obtain data from more users than a scale used in aconsumer setting.

The scale can also be in a combination consumer/professional mode. Acombination consumer/professional mode includes a scale as used and/oroperated in a consumer setting for purposes and/or uses by aprofessional, and/or in a professional setting for purposes and/or usesby the consumer (e.g., use by the consumer outside of the professionalsetting and/or in addition to). As a specific example, a scale islocated at a user's dwelling and used by multiple family members. Afirst user of the family is diagnosed with a heart-related condition andthe doctor may offer a service to review data from the scale (andoptionally another user device) of the first user. When the other familymembers stand on the scale, the scale operates in the consumer mode. Theother family members may or may not have the service activated for thedoctor to review data and the scale operates via the consumer mode. Whenthe first user that is diagnosed with heart-related condition stands onthe scale, the scale recognizes the user and operates in a professionalmode or a combination mode. For example, the scale outputs aggregateddata from the scale to external circuitry that is accessible by thedoctor of the first user.

Data provided to the user and/or the professional can default to bedisplayed on the user interface of the scale, the GUI of the userdevice, and/or a GUI of other external circuitry depending on the use ofthe scale. In a consumer mode and/or combination consumer/professionalmode, data can default to display on the user interface of the scale.The defaulted display of data can be revised by the user providinginputs to display the data on the GUI of a user device or a GUI ofanother external circuitry (e.g., a standalone CPU) and/or automaticallyby the scale based on past scale-based actions of the user. As aspecific example, a first user provided a user input to the scale todisplay data on the GUI of the user device multiple times (e.g., morethan a threshold number of times, such as five times). In response, thescale adjusts the defaulted display and output data to the GUI of theuser device. The display on the user interface of the scale and/or GUIof the user device (or other external circuitry) can include anindication of available additional health information, requests forcategories of interest, and/or the additional health information, amongother displays. In a professional mode, the scale is not owned by theuser. The user may be uninterested in synchronizing their user devicewith the professional's scale. The display may default to the GUI of theuser device to display an option to synchronize, and/or to override thesynchrony. Alternatively, the display may default to the user interfaceof the scale to display an option to synchronize and, responsive to userverification or authority to synchronize, defaults to display on the GUIof the user device. During the combination consumer/professional mode,portions of scale-obtained data for a particular user may default todisplay on external circuitry, such as a standalone or server CPU thatis accessible by the professional.

FIG. 1c shows an example of a scale wireless communicating with externalcircuitry consistent with aspects of the present disclosure. The scaleis configured to monitor signals and/or data indicative of physiologicparameters of the user while the user is standing on the platform 101and communicate the signals and/or data to the external circuitry 111.

As discussed above, a scale in various embodiments includes a platform101, a user display 102, processing circuitry 104 include a plurality ofelectrodes, and output circuitry. The output circuitry is configured andarranged to send user data to the external circuitry 111 for assessmentat a remote location. The external circuitry 111 is not integratedwithin the scale. The scale communicates user data wirelessly (and/orvia the cloud 123) to and from the external circuitry 111. For example,the external circuitry 111 can determine at least one physiologicparameter. In some embodiments, the external circuitry 111 optionallycontrols access to the physiologic parameter by storing the parameter ina database corresponding with and/or integrated with the externalcircuitry 111. Alternatively and/or in addition (such as, in response todetermining the user can access the parameter) the external circuitry111 outputs the physiologic parameter to the scale for display and/orstorage.

In various embodiments, the scale outputs user input data that providesan indication that the user is interested in additional healthinformation and various categories of interest. As previously discussed,the categories of interest can include demographics of interest,symptoms of interest, disorders of interest, diseases of interest, drugsof interest, treatments of interest, etc. The additional healthinformation can be derived by the external circuitry 111 and provided tothe scale that correlates to the category of interest and a physiologicparameter of the user.

For example, as illustrated by FIG. 1c , the user provides userinput/outputs to the scale. The inputs/outputs include the categories ofinterest. The scale obtains signals using the data-procurement circuitryand outputs user-weight to the user. Further, the scale outputsscale-based physiological raw data (e.g., the collected signalsmanifested as user data indicative of the user's identity andcardio-physiological measurements). As illustrated, the output caninclude a wireless communication to the external circuitry 111 using acloud system 123. The external circuitry 111 validates the raw data asconcerning a specific user and determines at least one physiologicparameter. In various embodiments, the external circuitry 111 determinesclinical indications of the user. Further, the external circuitry 111generates additional health information by correlating the raw data withthe categories of interest and outputs the additional healthinformation. For example, the external circuitry 111 outputs theaddition health information to the scale and/or another user circuitryusing the cloud system 123 and/or another wireless communication.

The external circuitry 111, in various embodiments, validates thereceived user data as corresponding to a particular user and correlatesthe received user data with a profile of the user based onidentification metadata within the received user data and/or based onidentification of the user using the user data. For example, in someembodiments, the processing circuitry of the scale correlates theuser-corresponding data with the user data such that the user dataincludes identification metadata. The external circuitry 111 thenidentifies the user, validates the user data as corresponding to theuser, and identifies the profile corresponding to the user using theidentification metadata within the user data. The profile, in variousembodiments, is a user health profile, such as a medical history file.

In a number of embodiments, the external circuitry 111 provides (e.g.,determines) one or more physiologic parameters by processing the userdata, such as determining a physiologic parameter as discussed infurther detail herein. The physiologic parameters can include PWV, BCG,respiration, arterial stiffness, cardiac output, pre-ejection period,stroke volume, diagnosis, conditions, and risk factors, among otherhealth information. The external circuitry 111 provides the physiologicparameter, in some embodiments, by updating the profile of the user withthe received user data and/or the physiologic parameter.

In various related embodiments, the external circuitry 111 determinesadditional health information and provides the additional healthinformation to the scale for display to the user. The additional healthinformation can be indicative of the physiologic parameter and cancorrelate to categories of interest provided by the user. The categoriesof interest can be provided at a different time, the same time and/orfrom the scale. In various embodiments, the additional healthinformation is based on historical user data. For example, theadditional health information (e.g., a table) provided can include acorrelation to the category of interest and the user data over time.

In some embodiments, the external circuitry controls access to the userprofile and/or the data. In some embodiments, the control of accessincludes allowing access to the physiologic parameter and the user datato a physician corresponding to the user for information. Further, thecontrol includes not allowing access to the physiologic parameters tothe user. In various embodiments, the user is allowed to access the userdata in the profile and the scale can display portions of the user dataand/or other non-regulated data. Additionally, the external circuitry111 may not allow access to the profile and/or any data corresponding tothe profile to non-qualified personal, such as other users. In variousembodiments, the user is allowed access the physiologic parameter inresponse to interpretation by the physician and a prescription from thephysician to access the physiologic parameter. Further, in someembodiments, a demographic model and/or other report is provided to theuser in response to the physiologic parameter. For example, the user maynot be allowed to view the physiologic parameter but is provided genericinformation corresponding to other users with similar physiologicparameter value.

The access is controlled, in various embodiments, using a verificationprocess. For example, in response to verifying identification of thephysician and/or the user, access to particular data can be provided.The verification can be based on a user sign in and password, apassword, biometric data, etc., and/or identification of the user usingthe scale (in which, the relevant data is sent to the scale or anotheruser device in response to the identification).

In various embodiments, the physiologic parameter is provided as anadditional service. For example, the user can obtain the informationand/or have their physician interpret the information for a service fee.The service fee can include a one-time fee for a single interpretation,a monthly or yearly service fee, and/or can be a portion of a healthcare insurance fee (e.g., the user can purchase a health care plan thatincludes the service). In such embodiments, the physician correspondingto the user can access the physiologic parameter and/or other user datain response to verification that the user has enabled the service andverification of the identity of the physician.

The remote processing and/or controlled access, for example, allows aphysician corresponding with the data to access the physiologicparameter for interpretation. For example, the physician can give aprescription to the user to access all information in the user profile.In response to the prescription, the external circuitry 111 allows theuser to access the physiologic parameter. Further, the physician canprescribe medicine to the user based on the profile and the externalcircuitry 111 can provide an indication to the user that a prescriptionfor medicine is ready. The physician may provide instructions or furtherexplanation for the user, which can be sent and displayed using thescale and/or another user-device. Such information can includelife-style suggestions, explanation for how to use the prescribedmedicine and/or why it is prescribed, and/or other advice, such assymptoms that the user should watch for. For instance, the physiologicparameter may suggest that the user has a heart condition and/ordisorder. The physician may prescribe medicine to the user and/orprovide potential symptoms that the user should watch for and/or shouldgo to the physician's office or an emergency room if the symptoms arise.In this manner, the scale and controlled access to Rx health informationis used to remotely monitor health of the user and/or provide physicianservices.

In accordance with various embodiments, although not illustrated by FIG.1d , the apparatus includes an additional sensor circuitry that isexternal to the scale. The additional sensor circuitry can include acommunication circuit and is configured and arranged to engage the userwith electrical signals and collect therefrom signals indicative of anECG of the user. The sensor circuitry, which may include and/or becorrelated with processing circuitry configured to derive an ECG fromthe collected signals. The sensor circuitry communicates the ECG to theexternal circuitry 111 and the scale can communicate a BCG to theexternal circuitry 111.

In various embodiments, as illustrated by FIG. 1d , the apparatusincludes additional scales. For example, the external circuitry 111 canreceive user data from a plurality of scales. In some embodiments, oneor more of the scales are located at a physician's office, such as thephysician corresponding with the user. The external circuitry 111 canreceive user data from the scale located at the physician's office andcan calibrate the user data from the scale at the physician's officewith the user data from the scale corresponding the user. In this way,data obtained from both scales are relevant to one another.

FIG. 1d shows an example of apparatus including a plurality of scalesand external circuitry consistent with aspects of the presentdisclosure. As illustrated, the apparatus includes a plurality of scales129-1, 129-2 . . . 129-P (herein generally referred to as “the scales129”) and external circuitry 111. Each scale can include the scale,including the platform 101 and user display 102, as previouslyillustrated and discussed with regard to FIG. 1a . Thereby, each scaleincludes a platform, data-procurement circuitry 138 includingforce-sensor circuitry and plurality of electrodes which are integratedwith the data-procurement circuitry 138, processing circuitry 104 toreceive collected signals from the data-procurement circuitry 138 and,in response, derive and output user-data to the external circuitry 111.The processing circuitry 104 includes a CPU and a memory circuit withuser-corresponding data stored in the memory circuit. The user-data, invarious embodiments, is automatically sent from the scales 129 to theexternal circuitry 111.

In various embodiments, the apparatus is used to remotely determinephysiologic parameters (e.g., Rx health information) of a plurality ofusers. The scales 129, for example, correspond to the plurality ofusers. For example, each scale at block 116 waits for a user to stand onthe platform. User-corresponding data 103 is input and/or received priorto the user standing on the respective scale and/or in response to. Inresponse to the user standing on the respective scale, the respectivescale collects signals indicative of an identity of the user andcardio-physiological measurements (e.g., force signals). The processingcircuitry, at block 118, processes the signals and, in response, derivesand outputs user data to the external circuitry 111. For example, theprocessing circuitry of the scale, using the signals, derives andoutputs user-data corresponding to a particular user to the externalcircuitry 111 for assessment at a remote location that is not integratedwithin the scale.

As illustrated, the external circuitry 111 is configured to correlatethe user data with a specific user/user profile, determine physiologicparameters, and optionally control access to the physiologic parameters.In various embodiments, the external circuitry includescomputer-readable instructions executed to perform the variousfunctions. For example, as illustrated by FIG. 1d , the externalcircuitry includes correlation logic 131 to correlate the user data,physiologic parameter logic 132 to determine parameters, and accesscontrol logic 133 to control access, as described further herein.

The external circuitry 111 receives the user data that corresponds tothe plurality users from the plurality of scales 129. The respectiveuser data can be received at over-lapping times and/or separate times.In response to receiving the user data, the external circuitry 111, invarious embodiments, identifies the respective plurality of users basedon the user data and validates the user data as corresponding to theusers and, at block 127, correlates the received user data with profilesof the respective plurality of users based on the identification of theusers. In various embodiments, the users can be identified usingidentification metadata within the user data (e.g., user IDs). In anumber of embodiments, at block 119, the external circuitry 111 provides(e.g., determines) the physiologic parameters by processing the userdata. The external circuitry 111 provides the physiologic parameters, insome embodiments, by updating the profile of the user with the user dataand/or the physiologic parameter (s) at block 122. Alternatively, insome embodiments, the physiologic parameter(s) are output to therespective scale.

In accordance with various embodiments, at block 126, the externalcircuitry optionally controls access to the user profile. The control ofaccess can include allowing access to the physiologic parameter (e.g., aclinical indication) and the user-data to at least one physiciancorresponding to at least one of the plurality of users and forinterpretation. Further, the control includes not allowing access to thephysiologic parameter(s) to the plurality of users (e.g., without aprescription). In various embodiments, the users are allowed access tothe user data in the profile and the scale can display portions of theuser data and/or other non-regulated data. In various embodiments, aspecific user among the plurality of users is allowed access to thephysiologic parameter corresponding to the specific user in response tointerpretation by a physician corresponding to the specific user and aprescription from the physician to access the physiologic parameter.Further, in some embodiments, a demographic model and/or other report isprovided to one or more users in response to the physiologic parameterand/or categories of interest input by the user.

In various embodiments, the controlled access allows a physiciancorresponding with one or more of the users to access the physiologicparameter for interpretation. For example, the physician can give aprescription to the user to access all information in the user profile.In response to the prescription, the external circuitry 111 allows theuser to access the physiologic parameter and/or outputs the physiologicparameter to the respective scale (and/or other user device)corresponding to the user for display. Further, the physician canprescribe medicine to the user based on the profile and the externalcircuitry 111 can provide an indication to the user that a prescriptionfor medicine is ready. The physician may prescribe medicine to the userand/or provide potential symptoms that the user should watch for.

As such, and in accordance with various embodiments, the one or morescales 129 have the capability to send raw force signals using wirelesscommunications and/or over the Internet. The raw force signals are sentto the external circuitry 111, which may be an online database, whereadvanced processing is performed using processing resources that may bemore powerful than the scale. The external circuitry 111 processes theforce signals to determine the physiologic parameters. The user mayaccess the one or more the physiologic parameters corresponding to theuser via a prescription from a physician and/or a prescription service.The service provider can, for example, allow the user's physician toaccess the physiologic parameter and other data for interpretation inresponse to the user paying a service fee. In response to the servicefee, the physician can interpret the data and may prescribe access tothe data, among other things. The external circuitry 111 and/or onlinedatabase/site can track user data for a plurality of users and from aplurality of scales and can correlate the user data with a profile ofthe respective user (e.g., using the access database 136 containingcorrelations or permissions to user profiles and the user-profile database 134 containing the user profiles and corresponding user data). Theprofile of the user can be updated over time. Access to each respectiveprofile is controlled and only allowed to the user's physician. Theuser's physician can be identified upon establishing the profile withthe service provider and/or upon initializing the scale. For example,the user can purchase a scale over the counter and not pay for theservice. The scale and the service provider can track the relevant dataover time and allow access in response to a fee. Alternatively, theservice provider may discard the information (and not determine clinicalindications) until the service is established by the user.

In various embodiments, the external circuitry 111 provides a table tothe user that corresponds to the physiologic parameter and/or categoriesof interest. Such a table can include non-Rx health information.Alternatively, the table can include Rx health information provided tothe user in response to a prescription from a corresponding physician.

The remaining figures illustrate various ways to collect the physiologicdata from the user, electrode configurations, and alternative modes ofthe processing circuitry 104. For general and specific informationregarding the collection of physiologic data, electrode configurations,and alternative modes, reference is made to U.S. patent application Ser.No. 14/338,266 filed on Oct. 7, 2015, which is hereby fully incorporatedby references for its teachings.

FIG. 1e shows current paths 100 through the body of a user 105 standingon a scale 110 for the IPG trigger pulse and Foot IPG, consistent withvarious aspects of the present disclosure. Impedance measurements 115are measured when the user 105 is standing and wearing coverings overthe feet (e.g., socks or shoes), within the practical limitations ofcapacitive-based impedance sensing, with energy limits considered safefor human use. The measurements 115 can be made with non-clothingmaterial placed between the user's bare feet and contact electrodes,such as thin films or sheets of plastic, glass, paper or wax paper,whereby the electrodes operate within energy limits considered safe forhuman use. The IPG measurements can be sensed in the presence ofcallouses on the user's feet that normally diminish the quality of thesignal.

As shown in FIG. 1e , the user 105 is standing on a scale 110, where thetissues of the user's body will be modeled as a series of impedanceelements, and where the time-varying impedance elements change inresponse to cardiovascular and non-cardiovascular movements of the user.ECG and IPG measurements sensed through the feet can be challenging totake due to small impedance signals with (1) low SNR, and because theyare (2) frequently masked or distorted by other electrical activity inthe body such as the muscle firings in the legs to maintain balance. Thehuman body is unsteady while standing still, and constant changes inweight distribution occur to maintain balance. As such, cardiovascularsignals that are measured with weighing scale-based sensors typicallyyield signals with poor SNR, such as the Foot IPG and standing BCG.Thus, such scale-based signals require a stable and high qualitysynchronous timing reference, to segment individual heartbeat-relatedsignals for signal averaging to yield an averaged signal with higher SNRversus respective individual measurements.

The ECG can be used as the reference (or trigger) signal to segment aseries of heartbeat-related signals measured by secondary sensors(optical, electrical, magnetic, pressure, microwave, piezo, etc.) foraveraging a series of heartbeat-related signals together, to improve theSNR of the secondary measurement. The ECG has an intrinsically high SNRwhen measured with body-worn gel electrodes, or via dry electrodes onhandgrip sensors. In contrast, the ECG has a low SNR when measured usingfoot electrodes while standing on said scale platforms; unless the useris standing perfectly still to eliminate electrical noise from the legmuscles firing due to body motion. As such, ECG measurements at the feetwhile standing are considered to be an unreliable trigger signal (lowSNR). Therefore, it is often difficult to obtain a reliablecardiovascular trigger reference timing when using ECG sensorsincorporated in base scale platform devices. Both Inan, et al. (IEEETransactions on Information Technology in Biomedicine, 14:5, 1188-1196,2010) and Shin, et al. (Physiological Measurement, 30, 679-693, 2009)have shown that the ECG component of the electrical signal measuredbetween the two feet while standing was rapidly overpowered by theelectromyogram (EMG) signal resulting from the leg muscle activityinvolved in maintaining balance.

The accuracy of cardiovascular information obtained from weighing scalesis also influenced by measurement time. The number of beats obtainedfrom heartbeats for signal averaging is a function of measurement timeand heart rate. Typically, a resting heart rates range from 60 to 100beats per minute. Therefore, short signal acquisition periods may yielda low number of beats to average, which may cause measurementuncertainty, also known as the standard error in the mean (SEM). SEM isthe standard deviation of the sample mean estimate of a population mean.Where, SE is the standard error in the samples N, which is related tothe standard error or the population S. The following is an example SEfor uncorrelated noise:

${S\; E} = \frac{S}{\sqrt{N}}$For example, a five second signal acquisition period may yield a maximumof five to eight beats for ensemble averaging, while a 10 second signalacquisition could yield 10-16 beats. However, the number of beatsavailable for averaging and SNR determination is usually reduced for thefollowing factors; (1) truncation of the first and last ensemble beat inthe recording by the algorithm, (2) triggering beats falsely missed bytriggering algorithm, (3) cardiorespiratory variability, (4) excessivebody motion corrupting the trigger and Foot IPG signal, and (5) loss offoot contact with the measurement electrodes.

Sources of noise can require multiple solutions for SNR improvements forthe signal being averaged. Longer measurement times increase the numberof beats lost to truncation, false missed triggering, and excessivemotion. Longer measurement times also reduce variability fromcardiorespiratory effects. If shorter measurement times (e.g., less than30 seconds) are desired for scale-based sensor platforms, sensingimprovements need to tolerate body motion and loss of foot contact withthe measurement electrodes.

The human cardiovascular system includes a heart with four chambers,separated by valves that return blood to the heart from the venoussystem into the right side of the heart, through the pulmonarycirculation to oxygenate the blood, which then returns to the left sideof the heart, where the oxygenated blood is pressurized by the leftventricles and is pumped into the arterial circulation, where blood isdistributed to the organs and tissues to supply oxygen. Thecardiovascular or circulatory system is designed to ensure oxygenavailability and is often the limiting factor for cell survival. Theheart normally pumps five to six liters of blood every minute duringrest and maximum cardiac output during exercise increases up toseven-fold, by modulating heart rate and stroke volume. The factors thataffect heart rate include autonomic innervation, fitness level, age andhormones. Factors affecting stroke volume include heart size, fitnesslevel, contractility or pre-ejection period, ejection duration, preloador end-diastolic volume, afterload or systemic resistance. Thecardiovascular system is constantly adapting to maintain a homeostasis(set point) that minimizes the work done by the heart to maintaincardiac output. As such, blood pressure is continually adjusting tominimize work demands during rest. Cardiovascular disease encompasses avariety of abnormalities in (or that affect) the cardiovascular systemthat degrade the efficiency of the system, which include but are notlimited to chronically elevated blood pressure, elevated cholesterollevels, edema, endothelial dysfunction, arrhythmias, arterialstiffening, atherosclerosis, vascular wall thickening, stenosis,coronary artery disease, heart attack, stroke, renal dysfunction,enlarged heart, heart failure, diabetes, obesity and pulmonarydisorders.

Each cardiac cycle results in a pulse of blood being delivered into thearterial tree. The heart completes cycles of atrial systole, deliveringblood to the ventricles, followed by ventricular systole deliveringblood into the lungs and the systemic arterial circulation, where thediastole cycle begins. In early diastole the ventricles relax and fillwith blood, then in mid-diastole the atria and ventricles are relaxedand the ventricles continue to fill with blood. In late diastole, thesinoatrial node (the heart's pacemaker) depolarizes then contracting theatria, the ventricles are filled with more blood and the depolarizationthen reaches the atrioventricular node and enters the ventricular sidebeginning the systole phase. The ventricles contract and the blood ispumped from the ventricles to arteries.

The ECG is the measurement of the heart's electrical activity and isdescribed in five phases. The P-wave represents atrial depolarization,the PR interval is the time between the P-wave and the start of the QRScomplex. The QRS wave complex represents ventricular depolarization. TheQRS complex is the strongest wave in the ECG and is frequently used as atiming reference for the cardiovascular cycle. Atrial repolarization ismasked by the QRS complex. The ST interval represents the period of zeropotential between ventricular depolarization and repolarization. Thecycle concludes with the T-wave representing ventricular repolarization.

The blood ejected into the arteries creates vascular movements due tothe blood's momentum. The blood mass ejected by the heart first travelsheadward in the ascending aorta and travels around the aortic arch thentravels down the descending aorta. The diameter of the aorta increasesduring the systole phase due to the high compliance (low stiffness) ofthe aortic wall. Blood traveling in the descending aorta bifurcates inthe iliac branch which transitions into a stiffer arterial region due tothe muscular artery composition of the leg arteries. The blood pulsationcontinues down the leg and foot. Along the way, the arteries branch intoarteries of smaller diameter until reaching the capillary beds where thepulsatile blood flow turns into steady blood flow, delivering oxygen tothe tissues. The blood returns to the venous system terminating in thevena cava, where blood returns to the right atrium of the heart for thesubsequent cardiac cycle.

Surprisingly, high quality simultaneous recordings of the Leg IPG andFoot IPG are attainable in a practical manner (e.g., a user operatingthe device correctly simply by standing on the impedance body scale footelectrodes), and can be used to obtain reliable trigger fiducial timingsfrom the Leg IPG signal. This acquisition can be far less sensitive tomotion-induced noise from the Leg EMG that often compromises Leg ECGmeasurements. Furthermore, it has been discovered that interleaving thetwo Kelvin electrode pairs for a single foot, result in a design that isinsensitive to foot placement within the boundaries of the overallelectrode area. As such, the user is not constrained to comply withaccurate foot placement on conventional single foot Kelvin arrangements,which are highly prone to introducing motion artifacts into the IPGsignal, or result in a loss of contact if the foot is slightlymisaligned. Interleaved designs begin when one or more electrodesurfaces cross over a single imaginary boundary line separating anexcitation and sensing electrode pair. The interleaving is configured tomaintain uniform foot surface contact area on the excitation and sensingelectrode pair, regardless of the positioning of the foot over thecombined area of the electrode pair.

Various aspects of the present disclosure include a weighing scaleplatform (e.g., scale 110) of an area sufficient for an adult of averagesize to stand comfortably still and minimize postural swaying. Thenominal scale length (same orientation as foot length) is 12 inches andthe width is 12 inches. The width can be increased to be consistent withthe feet at shoulder width or slightly broader (e.g., 14 to 18 inches,respectively).

FIG. 1f is a flow chart depicting an example manner in which auser-specific physiologic meter or scale may be programmed in accordancewith the present disclosure. This flow chart uses a computer processorcircuit (or CPU) along with a memory circuit shown herein as userprofile memory 146 a. The CPU operates in a low-power consumption mode,which may be in off mode or a low-power sleep mode, and at least oneother higher power consumption mode of operation. The CPU can beintegrated with presence and/or motion sense circuits, such as a passiveinfrared (PIR) circuit and/or pyroelectric PIR circuit. In a typicalapplication, the PIR circuit provides a constant flow of data indicativeof amounts of radiation sensed in a field of view directed by the PIRcircuit. For instance, the PIR circuit can be installed behind an uppersurface which is transparent to infrared light (and/or other visiblelight) of the platform and installed at an angle so that the motion ofthe user approaching the platform apparatus is sensed. Radiation fromthe user, upon reaching a certain detectable level, wakes up the CPUwhich then transitions from the low-power mode, as depicted in block140, to a regular mode of operation. Alternatively, the low-power modeof operation is transitioned from a response to another remote/wirelessinput used as a presence to awaken the CPU. In other embodiments, usermotion can be detected by an accelerometer integrated in the scale orthe motion is sensed with a single integrated microphone or microphonearray, to detect the sounds of a user approaching.

Accordingly, from block 140, flow proceeds to block 142 where the useror other intrusion is sensed as data received at the platform apparatus.At block 144, the circuitry assesses whether the received data qualifiesas requiring a wake up. If not, flow turns to block 140. If however,wake up is required, flow proceeds from block 144 to block 146 where theCPU assesses whether a possible previous user has approached theplatform apparatus. This assessment is performed by the CPU accessingthe user profile memory 146A and comparing data stored therein for oneor more such previous users with criteria corresponding to the receiveddata that caused the wake up. Such criteria includes, for example, thetime of the day, the pace at which the user approached the platformapparatus as sensed by the motion detection circuitry, the height of theuser as indicated by the motion sensing circuitry and/or a camerainstalled and integrated with the CPU, and/or more sophisticatedbio-metric data provided by the user and/or automatically by thecircuitry in the platform apparatus.

As discussed herein, such sophisticated circuitry can include one ormore of the following user-specific attributes: foot length, type offoot arch, weight of user, and/or manner and speed at which the usersteps onto the platform apparatus or by user speech (e.g., voice). Insome embodiments, facial or body-feature recognition may also be used inconnection with the camera and comparisons of images therefrom to imagesin the user profile memory.

From block 146, flow proceeds to block 148 where the CPU obtains and/orupdates user corresponding data in the user profile memory. As alearning program is developed in the user profile memory, each accessand use of the platform apparatus is used to expand on the data andprofile for each such user. From block 148, flow proceeds to block 150where a decision is made regarding whether the set of electrodes at theupper surface of the platform are ready for the user, such as may bebased on the data obtained from the user profile memory. For example,delays may ensue from the user moving his or her feet about the uppersurface of the platform apparatus, as may occur while certain data isbeing retrieved by the CPU (whether internally or from an externalsource such as a program or configuration data updates from the Internetcloud) or when the user has stepped over the user display. If theelectrodes are not ready for the user, flow proceeds from block 150 toblock 152 to accommodate this delay.

Once the CPU determines that the electrodes are ready for use while theuser is standing on the platform surface, flow proceeds to block 160.Stabilization of the user on the platform surface may be ascertained byinjecting current through the electrodes via the interleaved arrangementthereof. Where such current is returned via other electrodes for aparticular foot and/or foot size, and is consistent for a relativelybrief period of time, for example, a few seconds, the CPU can assumethat the user is standing still and ready to use the electrodes andrelated circuitry. At block 160, a decision is made that both the userand the platform apparatus are ready for measuring impedance and certainsegments of the user's body, including at least one foot.

The remaining flow of FIG. 1f includes the application and sensing ofcurrent through the electrodes for finding the optimal electrodes (162)and for performing impedance measurements (block 164). Thesemeasurements are continued until completed at block 166 and all suchuseful measurements are recorded and are logged in the user profilememory for this specific user, at block 168. At block 172, the CPUgenerates output data to provide feedback as to the completion of themeasurements and, as can be indicated as a request via the user profilefor this user, as an overall report on the progress for the user andrelative to previous measurements made for this user has stored in theuser profile memory. Such feedback may be shown on the user display,through a speaker with co-located apertures in the platform for audiblereception by the user, and/or by vibration circuitry which, uponvibration under control of the CPU, the user can sense through one orboth feet while standing on the scale. From this output at block 172,flow returns to the low power mode as indicated at block 174 with thereturn to the beginning of the flow at the block 140.

FIG. 2a shows an example of the insensitivity to foot placement 200 onscale electrode pairs 205/210 with multiple excitation paths 220 andsensing current paths 215, consistent with various aspects of thepresent disclosure. An aspect of the platform is that it has a thicknessand strength to support a human adult of at least 200 pounds withoutfracturing, and another aspect of the device platform is comprised of atleast six electrodes, where the first electrode pair 205 is solid andthe second electrode pair 210 are interleaved. Another aspect is thefirst and second interleaved electrode pairs 205/210 are separated by adistance of at least 40+/−5 millimeters, where the nominal separation ofless than 40 millimeters has been shown to degrade the single Foot IPGsignal. Another key aspect is the electrode patterns are made frommaterials with low resistivity such as stainless steel, aluminum,hardened gold, ITO, index matched ITO (IMITO), carbon printedelectrodes, conductive tapes, silver-impregnated carbon printedelectrodes, conductive adhesives, and similar materials with resistivitylower than 300 ohms/sq. The resistivity can be below 150 ohms/sq. Theelectrodes are connected to the electronic circuitry in the scale byrouting the electrodes around the edges of the scale to the surfacebelow, or through at least one hole in the scale (e.g., a via hole).

Suitable electrode arrangements for dual Foot IPG measurements can berealized in other embodiments. In certain embodiments, the interleavedelectrodes are patterned on the reverse side of a thin piece (e.g., lessthan 2 mm) of high-ion-exchange (HIE) glass, which is attached to ascale substrate and used in capacitive sensing mode. In certainembodiments, the interleaved electrodes are patterned onto a thin pieceof paper or plastic which can be rolled up or folded for easy storage.In certain embodiments, the interleaved electrodes are integrated ontothe surface of a tablet computer for portable IPG measurements. Incertain embodiments, the interleaved electrodes are patterned onto akapton substrate that is used as a flex circuit.

In certain embodiments, the scale area has a length of 10 inches with awidth of eight inches for a miniature scale platform. Alternatively, thescale may be larger (up to 36 inches wide) for use in bariatric classscales.

In the present disclosure, the leg and foot impedance measurements canbe simultaneously carried out using a multi-frequency approach, in whichthe leg and foot impedances are excited by currents modulated at two ormore different frequencies, and the resulting voltages are selectivelymeasured using a synchronous demodulator as shown in FIG. 3a . Thishomodyning approach can be used to separate signals (in this case, thevoltage drop due to the imposed current) with very high accuracy andselectivity.

This measurement configuration is based on a four-point configuration inorder to minimize the impact of the contact resistance between theelectrode and the foot, a practice well-known in the art of impedancemeasurement. In this configuration the current is injected from a set oftwo electrodes (the “injection” and “return” electrodes), and thevoltage drop resulting from the passage of this current through theresistance is sensed by two separate electrodes (the “sense”electrodes), usually located in the path of the current. Since the senseelectrodes are not carrying any current (by virtue of their connectionto a high-impedance differential amplifier), the contact impedance doesnot significantly alter the sensed voltage.

In order to sense two distinct segments of the body (the legs and thefoot), two separate current paths are defined by electrode positioning.Therefore two injection electrodes are used, each connected to a currentsource modulated at a different frequency. The injection electrode forleg impedance is located under the plantar region of the left foot,while the injection electrode for the Foot IPG is located under the heelof the right foot. Both current sources share the same return electrodelocated under the plantar region of the right foot. This is anillustrative example. Other configurations may be used.

The sensing electrodes can be localized so as to sense the correspondingsegments. Leg IPG sensing electrodes are located under the heels of eachfoot, while the two foot sensing electrodes are located under the heeland plantar areas of the right foot. The inter-digitated nature of theright foot electrodes ensures a four-point contact for proper impedancemeasurement, irrespectively of the foot position, as already explained.

FIG. 2b shows an example of electrode configurations, consistent withvarious aspects of the disclosure. As shown by the electrodeconnections, in some embodiments, ground is coupled to the heel of onefoot of the user (e.g., the right foot) and the foot current injection(e.g., excitation paths 220) is coupled to the toes of the respectiveone foot (e.g., toes of the right foot). The leg current injection iscoupled to the toes of the other foot (e.g., toes of the left foot).

FIG. 2c shows an example of electrode configurations, consistent withvarious aspects of the disclosure. As shown by the electrodeconnections, in some embodiments, ground is coupled to the heel of onefoot of the user (e.g., the right foot) and the foot current injection(e.g., excitation paths 220) is coupled to the toes of the one foot(e.g., toes of the right foot). The leg current injection is coupled tothe heels of the other foot of the user (e.g., heels of the left foot).

FIGS. 3a-3b show example block diagrams depicting the circuitry forsensing and measuring the cardiovascular time-varying IPG raw signalsand steps to obtain a filtered IPG waveform, consistent with variousaspects of the present disclosure. The example block diagrams shown inFIGS. 3a-3b are separated in to a leg impedance sub-circuit 300 and afoot impedance sub-circuit 305.

Excitation is provided by way of an excitation waveform circuit 310. Theexcitation waveform circuit 310 provides a stable amplitude excitationsignal by way of various wave shapes of various, frequencies, such asmore specifically, a sine wave signal (as is shown in FIG. 3a ) or, morespecifically, a square wave signal (as shown in FIG. 3b ). Thisexcitation waveform (of sine, square, or other wave shape) is fed to avoltage-controlled current source circuit 315 which scales the signal tothe desired current amplitude. The generated current is passed through adecoupling capacitor (for safety) to the excitation electrode, andreturned to ground through the return electrode (grounded-loadconfiguration). Amplitudes of 1 and 4 mA peak-to-peak are typically usedfor Leg and Foot IPGs, respectively.

The voltage drop across the segment of interest (legs or foot) is sensedusing an instrumentation differential amplifier (e.g., Analog DevicesAD8421) 320. The sense electrodes on the scale are AC-coupled to theinputs of the differential amplifier 320 (configured for unity gain),and any residual DC offset is removed with a DC restoration circuit (asexemplified in Burr-Brown App Note Application Bulletin, SBOA003, 1991,or Burr-Brown/Texas Instruments INA118 datasheet). Alternatively, afully differential input amplification stage can be used whicheliminates the need for DC restoration.

The signal is then demodulated with a phase-sensitive synchronousdemodulator circuit 325. The demodulation is achieved in this example bymultiplying the signal by 1 or −1 synchronously in-phase with thecurrent excitation. Such alternating gain is provided by an operationalamplifier (op amp) and an analog switch (SPST), such as an ADG442 fromAnalog Devices). More specifically, the signal is connected to bothpositive and negative inputs through 10 kOhm resistors. The output isconnected to the negative input with a 10 kOhm resistor as well, and theswitch is connected between the ground and the positive input of the opamp. When open, the gain of the stage is unity. When closed (positiveinput grounded), the stage acts as an inverting amplifier with a gain of−1. Further, fully differential demodulators can alternatively be usedwhich employ pairs of DPST analog switches whose configuration canprovide the benefits of balanced signals and cancellation of chargeinjection artifacts. Alternatively, other demodulators such as analogmultipliers or mixers can be used. The in-phase synchronous detectionallows the demodulator to be sensitive to only the real, resistivecomponent of the leg or foot impedance, thereby rejecting any imaginary,capacitive components which may arise from parasitic elements associatedwith the foot to electrode contacts.

Once demodulated, the signal is band-pass filtered (0.4-80 Hz) with aband-pass filter circuit 330 before being amplified with a gain of 100with a non-inverting amplifier circuit 335 (e.g., using an LT1058operational amplifier from Linear Technology Inc.). The amplified signalis further amplified by 10 and low-pass filtered (cut-off at 20 Hz)using a low-pass filter circuit 340 such as 2-pole Sallen-Key filterstage with gain. The signal is then ready for digitization and furtherprocessing. In certain embodiments, the signal from the demodulatorcircuit 325 can be passed through an additional low-pass filter circuit345 to determine body or foot impedance.

In certain embodiments, the generation of the excitation voltage signal,of appropriate frequency and amplitude, is carried out by amicrocontroller, such as an MSP430 (Texas Instruments, Inc.) or aPIC18Fxx series (Microchip Technology, Inc.). The voltage waveform canbe generated using the on-chip timers and digital input/outputs or pulsewidth modulation (PWM) peripherals, and scaled down to the appropriatevoltage through fixed resistive dividers, active attenuators/amplifiersusing on-chip or off-chip operational amplifiers, as well asprogrammable gain amplifiers or programmable resistors. In certainembodiments, the generation of the excitation frequency signal can beaccomplished by an independent quartz crystal oscillator whose output isfrequency divided down by a series of toggle flip-flops (such as anECS-100AC from ECS International, Inc., and a CD4024 from TexasInstruments, Inc.). In certain embodiments, the generation of the waveshape and frequency can be accomplished by a direct digital synthesis(DDS) integrated circuit (such as an AD9838 from Analog Devices, Inc.).In certain embodiments, the generation of the wave shape (either sine orsquare) and frequency can be accomplished by a voltage-controlledoscillator (VCO) which is controlled by a digital microcontroller, orwhich is part of a phase-locked loop (PLL) frequency control circuit.Alternatively, the waveforms and frequencies can be directly generatedby on- or off-chip digital-to-analog converters (DACs).

In certain embodiments, the shape of the excitation is not square, butsinusoidal. Such configuration can reduce the requirements on bandwidthand slew rate for the current source and instrumentation amplifier.Harmonics, potentially leading to higher electromagnetic interference(EMI), can also be reduced. Such excitation may also reduce electronicsnoise on the circuit itself. Lastly, the lack of harmonics from sinewave excitation may provide a more flexible selection of frequencies ina multi-frequency impedance system, as excitation waveforms have feweropportunities to interfere between each other. Due to the concentrationof energy in the fundamental frequency, sine wave excitation could alsobe more power-efficient. In certain embodiments, the shape of theexcitation is not square, but trapezoidal. Alternatively, raised cosinepulses (RCPs) could be used as the excitation wave shape, providing anintermediate between sine and square waves. RCPs could provide higherexcitation energy content for a given amplitude, but with greatlyreduced higher harmonics.

To further reduce potential electromagnetic interference (EMI), otherstrategies may be used, such as by dithering the square wave signal(i.e., introducing jitter in the edges following a fixed or randompattern) which leads to so-called spread spectrum signals, in which theenergy is not localized at one specific frequency (or a set ofharmonics), but rather distributed around a frequency (or a set ofharmonics). Because of the synchronous demodulation scheme,phase-to-phase variability introduced by spread-spectrum techniques willnot affect the impedance measurement. Such a spread-spectrum signal canbe generated by, but not limited to, specialized circuits (e.g., MaximMAX31C80, SiTime SiT9001), or generic microcontrollers (see ApplicationReport SLAA291, Texas Instruments, Inc.). These spread-spectrumtechniques can be combined with clock dividers to generate lowerfrequencies as well.

As may be clear to one skilled in the art, these methods of simultaneousmeasurement of impedance in the leg and foot can be used for standardBody Impedance Analysis (BIA), aiming at extracting the relative contentof total water, free-water, fat mass and other body compositionmeasures. Impedance measurements for BIA are typically done atfrequencies ranging from kilohertz up to several megahertz. Themulti-frequency synchronous detection measurement methods describedabove can readily be used for such BIA, provided that low-pass filtering(345, FIGS. 3a and 3b ) instead of band-pass filtering (330, FIGS. 3aand 3b ) is performed following the demodulation. In certainembodiments, a separate demodulator channel may be driven by thequadrature phase of the excitation signal to allow the imaginarycomponent of the body impedance to be extracted in addition to the realcomponent. A more accurate BIA can be achieved by measuring both thereal and imaginary components of the impedance. This multi-frequencytechnique can be combined with traditional sequential measurements usedfor BIA, in which the impedance is measured at several frequenciessequentially. These measurements are repeated in several body segmentsfor segmental BIAs, using a switch matrix to drive the current into thedesired body segments.

While FIG. 2a shows a circuit and electrode configuration suitable tomeasure two different segments (legs and one foot), this approach is notreadily extendable to more segments due to the shared current returnelectrode (ground). To overcome this limitation, and providesimultaneous measurements in both feet, the system can be augmented withanalog switches to provide time-multiplexing of the impedancemeasurements in the different segments. This multiplexing can be aone-time sequencing (each segment is measured once), or interleaved at ahigh-enough frequency that the signal can be simultaneously measured oneach segment. The minimum multiplexing rate for proper reconstruction istwice the bandwidth of the measured signal, based on signal processingtheory (the Nyquist rate), which equals to about 100 Hz for theimpedance signal considered here. The rate must also allow for thesignal path to settle in between switching, which usually limits themaximum multiplexing rate. Referring to FIG. 14a , one cycle might startthe measurement of the leg impedance and left foot impedances (similarlyto previously described, sharing a common return electrode), but thenfollow with a measurement of the right foot after reconfiguring theswitches. For specific information regarding typical switchconfigurations, reference to U.S. patent application Ser. No. 14/338,266filed on Oct. 7, 2015, which is fully incorporated for its specific andgeneral teaching of switch configurations.

Since right and left feet are measured sequentially, one should notethat a unique current source (at the same frequency) may be used tomeasure both, providing that the current source is not connected to thetwo feet simultaneously through the switches, in which case the currentwould be divided between two paths. One should also note that afully-sequential measurement, using a single current source (at a singlefrequency) successively connected to the three different injectionelectrodes, could be used as well, with the proper switch configurationsequence (no splitting of the current path).

In certain embodiments, the measurement of various body segments, and inparticular the legs, right foot and left foot, is achievedsimultaneously due to as many floating current sources as segments to bemeasured, running at separate frequencies so they can individually bedemodulated. Such configuration is exemplified in FIG. 14b for threesegments (legs, right and left feet). Such configuration has theadvantage to provide true simultaneous measurements without the addedcomplexity of time-multiplexing/demultiplexing, and associated switchingcircuitry. An example of such a floating current source is found inPlickett, et al., Physiological Measurement, 32 (2011). Another approachto floating current sources is the use of transformer-coupled currentsources (as depicted in FIG. 14c ). Using transformers to inject currentinto the electrodes enables the use of simpler, grounded-load currentsources on the primary, while the electrodes are connected to thesecondary. The transformer turns ratio can typically be 1:1, and sincefrequencies of interest for impedance measurement are typically in the10-1000 kHz (occasionally 1 kHz for BIA), relatively small pulsetransformers can be used. In order to limit the common mode voltage ofthe body, one of the electrodes in contact with the foot can begrounded.

While certain embodiments presented in the above specification have usedcurrent sources for excitation, the excitation can also be performed bya voltage source, where the resulting injection current is monitored bya current sense circuit so that impedance can still be derived by theratio of the sensed voltage (on the sense electrodes) over the sensedcurrent (injected in the excitation electrodes). It should be noted thatbroadband spectroscopy methods could also be used for measuringimpedances at several frequencies. Combined with time-multiplexing andcurrent switching described above, multi-segment broadband spectroscopycan be achieved.

Various aspects of the present disclosure are directed toward robusttiming extraction of the blood pressure pulse in the foot which isachieved by means of a two-step processing. In a first step, the usuallyhigh-SNR Leg IPG is used to derive a reference (trigger) timing for eachheart pulse. In a second step, a specific timing in the lower-SNR FootIPG is extracted by detecting its associated feature within a restrictedwindow of time around the timing of the Leg IPG.

Consistent with yet further embodiments of the present disclosure, FIG.3c depicts an example block diagram of circuitry for operating corecircuits and modules, including, for example, the operation of the CPUas in FIG. 1a with the related more specific circuit blocks/modules inFIGS. 3A-3B. As shown in the center of FIG. 3c , the computer circuit370 is shown with other previously-mentioned circuitry in a generalizedmanner without showing some of the detailed circuitry (e.g.,amplification and current injection/sensing (372)). The computer circuit370 can be used as a control circuit with an internal memory circuit (oras integrated with the memory circuit for the user profile memory 146Aof FIG. 1a ) for causing, processing and/or receiving sensed inputsignals as at block 372. As discussed, these sensed signals can beresponsive to injection current and/or these signals can be sensed byless complex grid-based sense circuitry surrounding the platform as isconvention in capacitive touch-screen surfaces which, in certainembodiments, the platform includes.

As noted, the memory circuit can be used not only for the user profilememory, but also as to provide configuration and/or program code and/orother data such as user-specific data from another authorized sourcesuch as from a user monitoring his/her logged data and/or profile from aremote desk-top. The remote device or desk-top can communicate with andaccess such data via a wireless communication circuit 376. For example,the wireless communication circuit 376 provides an interface between anapp on the user's cellular telephone/tablet and the apparatus, wherefromthe IPhone is the output/input interface for the platform (scale)apparatus including, for example, an output display, speaker and/ormicrophone, and vibration circuitry; each of these I/O aspects andcomponents being discussed herein in connection with other exampleembodiments.

A camera 378 and image encoder circuit 380 (with compression and relatedfeatures) can also be incorporated as an option. As discussed above, theweighing scale components, as in block 382, are also optionally includedin the housing which encloses and/or surrounds the platform.

For long-lasting battery life in the platform apparatus (batteries notshown), at least the CPU 370, the wireless communication circuit 376,and other current draining circuits are inactive unless and untilactivated in response to the intrusion/sense circuitry 388. As shown,one specific implementation employs a Conexant chip (e.g., CX93510) toassist in the low-power operation. This type of circuitry is designedfor motion sensors configured with a camera for visual verification andimage and video monitoring applications (such as by supporting JPEG andMJPEG image compression and processing for both color and black andwhite images). When combined with an external CMOS sensor, the chipretrieves and stores compressed JPEG and audio data in an on-chip memorycircuit (e.g., 256 KB/128 KB frame buffer) to alleviate the necessity ofexternal memory. The chip uses a simple register set via themicroprocessor interface and allows for wide flexibility in terms ofcompatible operation with another microprocessor.

In one specific embodiment, a method of using the platform with theplurality of electrodes are concurrently contacting a limb of the user,includes operating such to automatically obtain measurement signals fromthe plurality of electrodes. As noted above, these measurement signalsmight initially be through less complex (e.g., capacitive grid-type)sense circuitry. Before or while obtaining a plurality of measurementsignals by operating the circuitry, the signal-sense circuitry 388 isused to sense wireless-signals indicative of the user approaching theplatform and, in response, causing the CPU circuitry 370 to transitionfrom a reduced power-consumption mode of operation and at least onehigher power-consumption mode of operation. After the circuitry isoperating in the higher power-consumption mode of operation, the CPUaccesses the user-corresponding data stored in the memory circuit andcauses a plurality of impedance-measurement signals to be obtained byusing the plurality of electrodes while they are contacting the user viathe platform; therefrom, the CPU generates signals corresponding tocardiovascular timings of the user.

The signal-sense circuit can be employed as a passive infrared detectorand with the CPU programmed (as a separate module) to evaluate whetherradiation from the passive infrared detector is indicative of a human.For example, sensed levels of radiation that corresponds to a livebeing, such as a dog, that is less than a three-foot height, and/or hasnot moved for more than a couple seconds, can be assessed as being anon-human.

Accordingly, as the user is recognized as being human, the CPU isactivated and begins to attempt the discernment process of which usermight be approaching. This is performed by the CPU accessing theuser-corresponding data stored in the memory circuit (the user profilememory). If the user is recognized based on parameters such as discussedabove (e.g., time of morning, speed of approach, etc.), the CPU can alsoselect one of a plurality of different types of user-discerniblevisual/audible/tactile information and for presenting the discerned userwith visual/audible/tactile information that was retrieved from thememory as being specific to the user. For example, user-selectedvisual/audible data can be outputted for the user. Also, responsive tothe motion detection indication, the camera can be activated to captureat least one image of the user while the user is approaching theplatform (and/or while the user is on the platform to log confirmationof the same user with the measured impedance information). As shown inblock 374 of FIG. 3c , where a speaker is also integrated with the CPU,the user can simply command the platform apparatus to start the processand activation proceeds. As previously discussed, the scale can includevoice input/output circuitry to receive the user commands via voicecommands.

In another method, the circuitry of FIG. 3c is used with the electrodesbeing interleaved and engaging the user, as a combination weighing scale(via block 382) and a physiologic user-specific impedance-measurementdevice. By using the impedance-measurement signals and obtaining atleast two impedance-measurement signals between one foot of the user andanother location of the user, the interleaved electrodes assist the CPUin providing measurement results that indicate one or more of thefollowing user-specific attributes as being indicative or common to theuser: foot impedance, foot length, and type of arch, and wherein one ormore of the user-specific attributes are accessed in the memory circuitand identified as being specific to the user. This information can belater retrieved by the user, medical and/or security personnel,according to a data-access authorization protocol as might beestablished upon initial configuration for the user.

FIG. 3d shows an exemplary block diagram depicting the circuitry forinterpreting signals received from electrodes (e.g., 372 of FIG. 3c ),and/or CPU 370 of FIG. 3c . The input electrodes 375 transmit electricalsignals through the patient's body (depending on the desired biometricand physiological test to be conducted) and output electrodes 380receive the modified signal as affected by a user's electrical impedance385. Once received by the output electrodes 380, the modified signal isprocessed by processor circuitry 370 based on the selected test. Signalprocessing conducted by the processor circuitry 370 is discussed in moredetail above (with regard to FIGS. 3a-b ). In certain embodiments of thepresent disclosure, the circuitry within 370 is provided by TexasInstruments part #AFE4300.

FIG. 4 shows an example block diagram depicting signal processing stepsto obtain fiducial references from the individual Leg IPG “beats,” whichare subsequently used to obtain fiducials in the Foot IPG, consistentwith various aspects of the present disclosure. In the first step, asshown in block 400, the Leg IP and the Foot IPG are simultaneouslymeasured. As shown at 405, the Leg IPG is low-pass filtered at 20 Hzwith an 8-pole Butterworth filter, and inverted so that pulses have anupward peak. The location of the pulses is then determined by taking thederivative of this signal, integrating over a 100 ms moving window,zeroing the negative values, removing the large artifacts by zeroingvalues beyond 15× the median of the signal, zeroing the values below athreshold defined by the mean of the signal, and then searching forlocal maxima. Local maxima closer than a defined refractory period of300 ms to the preceding ones are dismissed. The result is a time seriesof pulse reference timings.

As is shown in 410, the foot IPG is low-pass filtered at 25 Hz with an8-pole Butterworth filter and inverted (so that pulses have an upwardpeak). Segments starting from the timings extracted (415) from the LegIPG (reference timings) and extending to 80% of the previous pulseinterval, but no longer than one second, are defined in the Foot IPG.This defines the time windows where the Foot IPG is expected to occur,avoiding misdetection outside of these windows. In each segment, thederivative of the signal is computed, and the point of maximum positivederivative (maximum acceleration) is extracted. The foot of the IPGsignal is then computed using an intersecting tangent method, where thefiducial (420) is defined by the intersection between a first tangent tothe IPG at the point of maximum positive derivative and a second tangentto the minimum of the IPG on the left of the maximum positive derivativewithin the segment.

The time series resulting from this two-step extraction is used withanother signal to facilitate further processing. These timings are usedas reference timings to improve the SNR of BCG signals to extractintervals between a timing of the BCG (typically the I-wave) and theFoot IPG for the purpose of computing the PWV, as previously disclosedin U.S. 2013/0310700 (Wiard). In certain embodiments, the timings of theLeg IPG are used as reference timings to improve the SNR of BCG signals,and the foot IPG timings are used to extract intervals between timingfiducials of the improved BCG (typically the I-wave) and the Foot IPGfor the purpose of computing the PTT and the (PWV).

In certain embodiments, the processing steps include an individual pulseSNR computation after individual timings are extracted, either in LegIPG or Foot IPG. Following the computation of the SNRs, pulses with aSNR below a threshold value are eliminated from the time series, toprevent propagating noise. The individual SNRs may be computed in avariety of methods known to one skilled in the art. For instance, anestimated pulse can be computed by ensemble averaging segments of signalaround the pulse reference timing. The noise associated with each pulseis defined as the difference between the pulse and the estimated pulse.The SNR is the ratio of the root-mean-square (RMS) value of theestimated pulse over the RMS value of the noise for that pulse.

In certain embodiments, the time interval between the Leg IPG pulses,and the Foot IPG pulses, also detected by the above-mentioned methods,is extracted. The Leg IPG measuring a pulse occurring earlier in thelegs compared to the pulse from the Foot IPG, the interval between thesetwo is related to the propagation speed in the lower body, i.e., theperipheral vasculature. This provides complementary information to theinterval extracted between the BCG and the Foot IPG for instance, and isused to decouple central versus peripheral vascular properties. It isalso complementary to information derived from timings between the BCGand the Leg ICG.

FIG. 5 shows an example flowchart depicting signal processing to segmentindividual Foot IPG “beats” to produce an averaged IPG waveform ofimproved SNR, which is subsequently used to determine the fiducial ofthe averaged Foot IPG, consistent with various aspects of the presentdisclosure. Similar to the method shown in FIG. 4, the Leg IP and theFoot IPG are simultaneously measured (500), the Leg IPG is low-passfiltered (505), the foot IPG is low-pass filtered (510), and segmentsstarting from the timings extracted (515) from the Leg IPG (referencetimings). The segments of the Foot IPG extracted based on the Leg IPGtimings are ensemble-averaged (520) to produce a higher SNR Foot IPGpulse. From this ensemble-averaged signal, the start of the pulse isextracted using the same intersecting tangent approach as describedearlier. This approach enables the extraction of accurate timings in theFoot IPG even if the impedance signal is dominated by noise, as shown inFIG. 7b . These timings are used together with timings extracted fromthe BCG for the purpose of computing the PTT and (PWV). Timings derivedfrom ensemble-averaged waveforms and individual waveforms can also beboth extracted, for the purpose of comparison, averaging anderror-detection.

Specific timings extracted from the IPG pulses (from either leg or foot)are related (but not limited) to the peak of the pulse, the minimumpreceding the peak, or the maximum second derivative (maximum rate ofacceleration) preceding the point of maximum derivative. An IPG pulseand the extraction of a fiducial (525) in the IPG can be performed byother signal processing methods, including (but not limited to) templatematching, cross-correlation, wavelet-decomposition, or short windowFourier transform.

FIG. 6a shows examples of the Leg IPG signal with fiducials (plot 600);the segmented Leg IPG into beats (plot 605); and the ensemble-averagedLeg IPG beat with fiducials and calculated SNR (plot 610), for anexemplary high-quality recording, consistent with various aspects of thepresent disclosure. FIG. 6b shows examples of the Foot IPG signal withfiducials derived from the Leg IPG fiducials (plot 600); the segmentedFoot IPG into beats (plot 605); and the ensemble-averaged Foot IPG beatwith fiducials and calculated SNR (plot 610), for an exemplaryhigh-quality recording, consistent with various aspects of the presentdisclosure.

FIG. 7a shows examples of the Leg IPG signal with fiducials (plot 700);the segmented Leg IPG into beats (plot 705); and the ensemble averagedLeg IPG beat with fiducials and calculated SNR (plot 710), for anexemplary low-quality recording, consistent with various aspects of thepresent disclosure.

FIG. 7b shows examples of the Foot IPG signal with fiducials derivedfrom the Leg IPG fiducials (plot 700); the segmented Foot IPG into beats(plot 705); and the ensemble-averaged Foot IPG beat with fiducials andcalculated SNR (plot 710), for an exemplary low-quality recording,consistent with aspects of the present disclosure.

FIG. 8 shows an example correlation plot 800 for the reliability inobtaining the low SNR Foot IPG pulse for a 30-second recording, usingthe first impedance signal as the trigger pulse, from a study including61 test subjects with various heart rates, consistent with variousaspects of the present disclosure.

In certain embodiments, a dual-Foot IPG is measured, allowing thedetection of blood pressure pulses in both feet. Such information can beused for diagnostic of peripheral arterial diseases (PAD) by comparingthe relative PATs in both feet to look for asymmetries. It can alsoincrease the robustness of the measurement by allowing one foot to havepoor contact with electrodes (or no contact at all). SNR measurementscan be used to assess the quality of the signal in each foot, and toselect the best one for downstream analysis. Timings extracted from eachfoot can be compared and set to flag potentially inaccurate PWVmeasurements due to arterial peripheral disease, in the event thesetimings are different by more than a threshold. Alternatively, timingsfrom both feet are pooled to increase the overall SNR if theirdifference is below the threshold.

In certain embodiments, the disclosure is used to measure a PWV, wherethe IPG is augmented by the addition of BCG sensing into the weighingscale to determine characteristic fiducials between the BCG and Leg IPGtrigger, or the BCG and Foot IPG. The BCG sensors are comprisedtypically of the same strain gage set used to determine the bodyweightof the user. The load cells are typically wired into a bridgeconfiguration to create a sensitive resistance change with smalldisplacements due to the ejection of the blood into the aorta, where thecirculatory or cardiovascular force produce movements within the body onthe nominal order of 1-3 Newtons. BCG forces can be greater than or lessthan the nominal range in cases such as high or low cardiac output.

FIGS. 9a-b show example configurations to obtain the PTT, using thefirst IPG as the triggering pulse for the Foot IPG and BCG, consistentwith various aspects of the present disclosure. The I-wave of the BCG900 normally depicts the headward force due to cardiac ejection of bloodinto the ascending aorta which is used as a timing fiducial indicativeof the pressure pulse initiation of the user's proximal aorta relativeto the user's heart. The J-wave is indicative of timings in the systolephase and also incorporates information related to the strength ofcardiac ejection and the ejection duration. The K-Wave provides systolicand vascular information of the user's aorta. The characteristic timingsof these and other BCG waves are used as fiducials that can be relatedto fiducials of the IPG signals of the present disclosure.

FIG. 10 shows nomenclature and relationships of various cardiovasculartimings, consistent with various aspects of the present disclosure.

FIG. 11 shows an example graph 1100 of PTT correlations for twodetection methods (white dots) Foot IPG only, and (black dots) Dual-IPGmethod, consistent with various aspects of the present disclosure.

FIG. 12 shows an example graph 1200 of PWV obtained from the presentdisclosure compared to the ages of 61 human test subjects, consistentwith various aspects of the present disclosure.

FIG. 13 shows an example of a scale 1300 with integrated foot electrodes1305 to inject and sense current from one foot to another foot, andwithin one foot.

FIG. 14a-c shows various examples of a scale 1400 with interleaved footelectrodes 1405 to inject/sense current from one foot to another foot,and measure Foot IPG signals in both feet.

FIGS. 15a-d shows an example breakdown of a scale 1500 with interleavedfoot electrodes 1505 to inject and sense current from one foot toanother foot, and within one foot.

FIG. 16 shows an example block diagram of circuit-based building blocks,consistent with various aspects of the present disclosure.

The various circuit-based building blocks shown in FIG. 16 can beimplemented in connection with the various aspects discussed herein. Inthe example shown, the block diagram includes foot electrodes 1600 thatcan collect the IPG signals. Further, the block diagram includes straingauges 1605, and an LED/photosensor 1610. The foot electrodes 1600 isconfigured with a leg impedance measurement circuit 1615, a footimpedance measurement circuit 1620, and an optional second footimpedance measurement circuit 1625. The leg impedance measurementcircuit 1615, the foot impedance measurement circuit 1620, and theoptional second foot impedance measurement circuit 1625 report themeasurements collected to a processor circuitry 1645.

The processor circuitry 1645 collects data from a weight measurementcircuit 1630 and an optional balance measurement circuit 1635 that areconfigured with the strain gauges 1605. Further, an optionalphotoplethysmogram (PPG) measurement circuit 1640, which collects datafrom the LED/photosensor 1610, provides data to the processor circuitry1645.

The processor circuitry 1645 is powered via a power circuit 1650.Further, the processor circuitry 1645 collects user input data from auser interface 1655 (e.g., iPad®, smart phone and/or other remote userhandy/CPU with a touch screen and/or buttons). The datacollected/measured by the processor circuitry 1645 is shown to the uservia a display 1660. Additionally, the data collected/measured by theprocessor circuitry 1645 can be stored in a memory circuit 1680.Further, the processor circuitry 1645 can optionally control a hapticfeedback circuit 1665, a speaker or buzzer 1670, a wired/wirelessinterface 1675, and an auxiliary sensor 1685 for one-way or two-waycommunication between the scale and the user.

FIG. 17 shows an example flow diagram, consistent with various aspectsof the present disclosure. At block 1700, a PWV length is entered. Atblock 1705, a user's weight, balance, leg, and foot impedance aremeasured. At 1710, the integrity of signals is checked (e.g., SNR). Ifthe signal integrity check is not met, the user's weight, balance, leg,and foot impedance are measured again (block 1705), if the signalsintegrity check is met, the leg impedance pulse timings are extracted(as is shown at block 1715). At block 1720, foot impedance and pulsetimings are extracted, and at block 1725, BCG timings are extracted. Atblock 1730, a timings quality check is performed. If the timings qualitycheck is not validated, the user's weight, balance, leg and footimpedance are again measured (block 1705). If the timings quality checkis validated, the PWV is calculated (as is shown at block 1735). Atblock 1740, the PWV is displayed to the user.

FIG. 18a shows an example scale 1800 communicatively coupled to awireless device, consistent with various aspects of the presentdisclosure. As described herein, a display 1805 displays the variousaspects measured by the scale 1800. The scale can also wirelesslybroadcast the measurements to a wireless device 1810. The wirelessdevice 1810 can also be implemented as an iPad®, smart phone or otherCPU to provide input data for configuring and operating the scale.

As an alternative or complementary user interface used in otherembodiments, the scale includes a foot-controlled user interface whichis enabled/implementable by one or more foot-based biometrics (forexample, with the user being correlated to previously-entered userweight, and/or foot size/shape). In certain embodiments, the userfoot-based biometric is also implemented by the user manually enteringdata (e.g., a password) on the upper surface or display area of thescale. In implementations in which the scale is configured with ahaptic, capacitive or flexible pressure-sensing upper surface, the(upper surface/tapping) touching from or by the user is sensed in theregion of the surface and processed according to conventional X-Y gridSignal processing in the logic circuitry/CPU that is within the scale.By using one or more of the accelerometers located within the scale atits corners, such user data entry is sensed by each such accelerometerso long as the user's toe, heel or foot pressure associated with eachtap provides sufficient force. Although the present discussion refers toa FUI, embodiments are not so limited. Various embodiments includeinternal or external GUIs that are in communication with the scale andused to obtain a biometric and that can be in place of the FUI and/or incombination with a FUI. For example, a user device having a GUI, such astablet, is in communication with the scale via a wired or wirelessconnection. The user device obtains a biometric, such a finger print,and communicates the biometric to the scale.

In various embodiments, the above discussed user-interface is used withother features described herein for the purpose of controlling access toRX health information and providing additional non-RX health informationsuch as: collecting the categories of interest input by the user, thebiometric and/or passwords entered by the user, displaying theadditional health information, and displaying an indication that RXhealth information can be accessed as a service or that additionalhealth information is available. For example, the user enters thecategories of interest to the scale using their foot and theuser-interface. The user data (e.g., RX health information or other userdata) might include less sensitive data (e.g., the user's weight) andmore sensitive data (e.g., the user's scale obtains cardiograms andother data generated by or provided to the scale and associated with theuser's symptoms and/or diagnoses). For data that may be moreuser-sensitive, the above described biometrics are used as directed bythe user for indicating and defining protocol to permit such data to beexported from the scale to other remote devices and/or for such data tobe displayed on the user-interface.

In some specific embodiments, the scale operates in different modes ofdata security and communication. The different modes of data securityand communication are enabled in response to biometrics identified bythe user and using the user-interface. In some embodiments, the scale isused by multiple users and/or the scale operates in different modes ofdata security and communication in response to identifying the user andbased on biometrics. The different modes of data security andcommunication include, for example: a first mode (e.g., default mode) inwhich the user's body mass and/or weight is displayed regardless of anybiometric which would associate with the specific user standing on thescale and no data is communicated to external circuitry; a second modein which complicated/more-sensitive data (or data reviewed infrequently)is only exported from the scale under specific manual commands providedto the scale under specific protocols and in response to a biometric;and third mode or modes in which the user-specific data that iscollected from the scale is processed and accessed based on the type ofdata and in response to a biometric. Such data categories includecategories of different levels of importance and/or sensitivities suchas the above-discussed high and low level data and other data that mightbe very specific to a symptom and/or degrees of likelihood fordiagnoses. Optionally, the CPU in the scale is also configured toprovide encryption of various levels of the user's sensitive data.

In some embodiments, the different modes of data security andcommunication are enabled in response to recognizing the user standingon the scale using a biometric and operating in a particular mode ofdata security and communication based on user preferences and/orservices activated. For example, the different modes of operationinclude the default mode (as discussed above) in which certain data(e.g., categories of interest, categories of user data, or historicaluser data) is not communicated from the scale to external circuitry, afirst communication mode in which data is communicated to externalcircuitry as identified in a user profile, a second or morecommunication modes in which data is communicated to a differentexternal circuitry for further processing. The different communicationmodes are enabled based on biometrics identified from the user and usersettings in a user profile corresponding with each user.

In a specific embodiment, a first user of the scale may not beidentified and/or have a user profile set up. In response to the firstuser standing on the scale, the scale operates in a default mode. Duringthe default mode, the scale displays the user's body mass and/or weighton the user display and does not output user data. A second user of thescale has a user profile set up that indicates the user would like datacommunicated to a computing device of the user. When the second userstands on the scale, the scale recognizes the second user based on abiometric and operates in a first communication mode. During the firstcommunication mode, the scale outputs at least a portion of the userdata to an identified external circuitry. For example, the firstcommunication mode allows the user to upload data from the scale to auser identified external circuitry (e.g., the computing device of theuser) that includes non-regulated health information. In the firstcommunication mode, the scale performs the processing of the raw sensordata and/or the external circuitry can. For example, the scale sends theraw sensor data and/or non-regulated health information to a computingdevice of the user. The computing device may not provide access to theraw sensor data to the user and/or can send the raw sensor data toanother external circuitry for further processing in response to a userinput. For example, the computing device can ask the user if the userwould like additional health information and/or regulated healthinformation as a service. In response to receiving an indication theuser would like the additional health information and/or regulatedhealth information, the computing device outputs the raw sensor dataand/or non-regulated health information to another external circuitryfor processing, providing to a physician for review, and controllingaccess, as discussed above.

In one or more additional communication modes, the scale outputs rawsensor data to an external circuitry for further processing. Forexample, during a second communication mode and a third communication,the scale sends the raw sensor data and other data to external circuitryfor processing. Using the above-provided example, a third user of thescale has a user profile set up that indicates the third user would likeadditional health information, such as non-regulated health informationbased on categories of interest. When the third user stands on thescale, the scale recognizes the third user based on one or morebiometrics and operates in a second communication mode. During thesecond communication mode, the scale outputs the raw sensor data to theexternal circuitry. The external circuitry processes the raw sensordata, determines at least one physiologic parameter of the user, andderives the additional health information. The external circuitry allowsaccess to the user to additional health information but does not allowthe user to access regulated health information, including thephysiologic parameter. For example, the regulated health information maynot be accessed by the third user until the third user has paid aservice fee and/or until a prescription by a physician is obtained. Insome embodiments, the external circuitry outputs the additional healthinformation and/or an indication that additional health information canbe accessed to the scale to display to the third user on the userinterface.

A fourth user of the scale has a user profile set up that indicates thefourth user has enabled a service to access regulated healthinformation. When the fourth user stands on the scale, the scalerecognizes the user based on one or more biometrics and operates in afourth communication mode. In the fourth communication mode, the scaleoutputs raw sensor data to the external circuitry, and the externalcircuitry processes the raw sensor data and controls access to the data.For example, the external circuitry may not allow access to theregulated health information until a physician reviews the information.In some embodiments, the external circuitry outputs data to the scale,in response to physician review. For example, the output data caninclude the regulated health information and/or an indication thatregulated health information is ready for review. The external circuitrymay be accessed by the user, using the scale and/or another user device.In some embodiments, using the foot-controlled user-interface of thescale, the scale displays the regulated health information to the user.In various embodiments, if the scale is unable to identify a particular(high security) biometric that enables the fourth communication mode,the scale may operate in a different communication mode and may stillrecognize the user. For example, the scale may operate in a defaultcommunication mode in which the user data collected by the scale isstored in a user profile corresponding to the fourth user and on thescale. In some related embodiments, the user data is output to theexternal circuitry at a different time.

Although the present embodiments illustrates a number of security andcommunication modes, embodiments in accordance with the presentdisclosure can include additional or fewer modes. Furthermore,embodiments are not limited to different modes based on different users.For example, a single user may enable different communication modes inresponse to particular biometrics of the user identified and/or based onuser settings in a user profile.

In various embodiments, the scale defines a user data table that definestypes of user data and sensitivity values of each type of user data. Inspecific embodiments, the user interface (e.g., FUI) displays the userdata table. In other specific embodiments a user interface of asmartphone, tablet, and/or other computing device displays the user datatable. For example, a wired or wireless tablet is used, in someembodiments, to display the user data table. The sensitivity values ofeach type of user data, in some embodiments, define in whichcommunication mode(s) the data type is communicated and/or whichbiometric is used to enable communication of the data type. In someembodiments, a default or pre-set user data table is displayed and theuser revises the user data table using the FUI. The revisions are inresponse to user inputs using the user's foot and/or contacting ormoving relative to the FUI. In a specific example, when the user standson the platform of the scale, and the scale detects touching of the toe,the scale can reject the toe touch (or tap) as a foot signal (e.g.,similar to wrist rejection for capacitive tablets with stylus). Althoughthe embodiments are not so limited, the above (and below) describedcontrol and display is provided using a wireless or wired tablet orother computing device as a user interface. The output to the wirelessor wired tablet, as well as additional external circuitry, is enabledusing biometrics. For example, the user is encouraged, in particularembodiments, to configure the scale with various biometrics. Thebiometric include scale-based biometrics and biometrics from the tabletor other user computing device. The biometric, in some embodiments, usedto enable output of data to the tablet and/or other external circuitryincludes a higher integrity biometric (e.g., higher likelihood ofidentifying the user accurately) than a biometric used to identify theuser and stored data on the scale.

Biometrics, as used herein, are metrics related to human characteristicsand used as a form of identification and access control. Scale-basedbiometrics includes biometrics that are obtained using signals collectedby the data-procurement circuitry of the scale (e.g., using electrodesand/or force sensors). Example scale-based biometrics include footlength, foot width, weight, voice recognition, facial recognition, apasscode tapped and/or picture drawn with a foot of the user on theFUI/GUI of the user display, among other biometrics. In some specificembodiments, a scale-based biometric includes a toe-print (e.g., similarto a finger print) that is recognized using a toe-print reader on theFUI/GUI of the scale. The toe print can be used as a secureidentification of the user. In other embodiments, the scale-basedbiometric includes a finger print captured using external circuitry incommunication with the scale (e.g., a cellphone or tablet having fingerprint recognition technology).

An example user data table is illustrated below:

Scale-stored Body Mass suggestions User-data Weight, local Index, userUser-Specific Physician-Provided (symptoms & Type weather specific newsAdvertisements Diagnosis/Report diagnosis) Sensitivity 1 3 5 10 9 (10 =highest, 1 = lowest)The above-displayed table is for illustrative purposes and embodimentsin accordance with the present disclosure can include additionaluser-data types than illustrated, such as cardiogram characteristics,clinical indications, physiologic parameters, user goals, demographicinformation, etc. In various embodiments, the user data table includesadditional rows than illustrated. The rows, in specific embodiments,include different data input sources and/or sub-data types (as discussedbelow). Data input sources include source of the data, such as physicianprovided, input from the Internet, user provided, from the externalcircuitry. The different data from the data input sources, in someembodiments, is used alone or in combination.

In various embodiments, the user adjusts the table displayed above torevise the sensitivity values of each data type. Further, although theabove-illustrated table includes a single sensitivity value for eachdata type, in various embodiments, one or more of the data types areseparated into sub-data types and each sub-data type has a sensitivityvalue. As an example, the user-specific advertisement is separated into:prescription advertisement, external device advertisements, exerciseadvertisements, and diet plan advertisement. Alternatively and/or inaddition, the sub-data types for user-specific advertisement includegeneric advertisements based on a demographic of the user andadvertisements in response to scale collected data (e.g., advertisementfor a device in response to physiologic parameters), as discussedfurther herein.

For example, weight data includes the user's weight and historicalweight as collected by the scale. In some embodiments, weight dataincludes historical trends of the user's weight and correlates todietary information and/or exercise information, among other user data.Body mass index data, includes the user's body mass index as determinedusing the user's weight collected by the scale and height. In someembodiments, similar to weight, body mass index data includes historytrends of the user's body mass index and correlates to various otheruser data.

User-specific advertisement data includes various prescriptions,exercise plans, dietary plans, and/or other user devices and/or sensorsfor purchase, among other advertisements. The user-specificadvertisements, in various embodiments, are correlated to input userdata and/or scale-obtained data. For example, the advertisements includegeneric advertisements that are relevant to the user based on ademographic of the user. Further, the advertisements includeadvertisements that are responsive to scale collected data (e.g.,physiologic parameter includes a symptom or problem and advertisement iscorrelated to the symptom or problem). A number of specific examplesinclude advertisements for beta blockers to slow heart rate,advertisements for a user wearable device (e.g., Fitbit®) to monitorheart rate, and advertisements for a marathon exercise program (such asin response to an indication the user is training for a marathon), etc.

Physician provided diagnosis/report data includes data provided by aphysician and, in various embodiments, is in responsive to the physicianreviewing the scale-obtained data. For example, the physician provideddiagnosis/report data includes diagnosis of a disorder/condition by aphysician, prescription medication prescribed by a physician, and/orreports of progress by a physician, among other data. In variousembodiments, the physician provided diagnosis/reports are provided tothe scale from external circuitry, which includes and/or accesses amedical profile of the user.

Scaled stored suggestion data includes data that provides suggestions oradvice for symptoms, diagnosis, and/or user goals. For example, thesuggestions include advice for training that is user specific (e.g.,exercise program based on user age, weight, and cardiogram data orexercise program for training for an event or reducing time to completean event, such as a marathon), suggestions for reducing symptomsincluding dietary, exercise, and sleep advice, and/or suggestions to seea physician, among other suggestions. Further, the suggestions or adviceinclude reminders regarding prescriptions. For example, based onphysician provided diagnosis/report data and/or user inputs, the scaleidentifies the user is taking a prescription medication. Theidentification includes the amount and timing of when the user takes themedication, in some embodiments. The scale reminds the user and/or asksfor verification of consumption of the prescription medication using thefoot-controlled user interface.

As further specific examples, recent discoveries may align and associatedifferent attributes of scale-based user data collected by the scale todifferent tools, advertisements, and physician provided diagnosis. Forexample, it has recently been discovered that atrial fibrillation ismore directly correlated with obesity. The scale collects various userdata and monitors weight and various components/symptoms of atrialfibrillation. In a specific embodiment, the scale recommends/suggests tothe user to: closely monitor weight, recommends a diet, goals for losingweight, correlates weight gain and losses for movement in cardiogramdata relative to arrhythmia. The movement in cardiogram data relative toarrhythmia, in specific embodiments, is related to atrial fibrillation.For example, atrial fibrillation is associated with indiscerniblep-waves and beat to beat fluctuations. Thereby, the scale correlatesweight gain/loss with changes in amplitude (e.g., discernibility) of ap-wave of a cardiogram (preceding a QRS complex) and changes in beat tobeat fluctuations.

FIG. 18b shows an example scale communicatively coupled to externalcircuitry and various data types provided to a user, consistent withvarious aspects of the present disclosure. The scale as illustrated byFIG. 18b includes the scale illustrated by FIG. 1a and/or FIG. 1b . Asillustrated, the apparatus includes a platform, a user display, aplatform for the user to stand on, data-procurement circuitry 138, andprocessing circuitry 104. The data-procurement circuitry 138 includesforce-sensor circuitry and a plurality of electrodes (e.g., thephysiologic sensors 108) which are integrated with the data-procurementcircuitry 138. As previously discussed, the scale includes an outputcircuit to send the user data to external circuitry 111. The externalcircuitry 111, in various embodiments, receives the user-data anddetermines the physiologic parameters of the user using the user data.

The various data types provided to the user, in some embodiments, areused to monitor atrial fibrillation. Atrial fibrillation, for example,causes additional problems, such as sleep deprivation and depression.Further, as discussed above, it has been recently discover that atrialfibrillation is more directly correlated to obesity and, in particular,to recent weight gains. As illustrated by FIG. 18b , at block 141,excess weight is reported by the scale. The excess weight, in someembodiments, includes an indication that the user is obese based on auser weight measured using the scale, and a height and age input by theuser. In various embodiments, the scale provides an indication of arecent increase of weight over a threshold value. In accordance with anumber of embodiments, the scale provides suggestions to the user, suchas goals for losing weight.

The excess weight causes, for some users, sleep apnea. As such, at block142, sleep apnea is reported to the scale by a sleep-circuit sensor, bya user, and/or as part of physician provided diagnosis/reports data. Thesleep-circuit sensor includes, in various embodiments, a smart bed orother user sensor circuitry (e.g., cell phone laying on the bed,Fitbit®, etc.) that measures cardiogram data and/or movement data whilethe user is sleeping. In various embodiments, whether or not the userhas sleep apnea is unknown by the scale. In such embodiments, at block142, the scale displays an advertisement for a sleep-circuit sensor tothe user using the foot-controlled user interface. Further, the scale,in some specific embodiments and in response to reporting of sleep apneainput to the scale, displays an advertisement for prescription medicinefor sleep apnea, treatments for sleep apnea, and/or a physician or studyfor sleep apnea, among other advertisements.

In various embodiments, sleep apnea causes sleep deprivation. At block143, in response to reporting of sleep apnea and/or an advertisement fora sleep-circuit sensor, the scale provides sleep deprivation suggestionsto the user. The sleep deprivation suggestions, in some embodiments,include suggestions to see a physician for sleep apnea, exercise advice,or dietary advice, among other suggestions. Sleep deprivation causesvarious other problems, such as heart problems, tiredness and slowmetabolism (which correlate to the excess weight of the user), and/orleads to prescription medication. Further, sleep deprivation causesdepression. At block 144, in response to the sleep deprivationsuggestions, the scale provides depression suggestions to the user, suchas using the FUI. The suggestions include prescription medicationssuggestions, exercise advice, suggestions to see a physician, amongother suggestions. Further, the scale, in some embodiments, providesadvertisements for specific depression prescription medication,physician specializing in depression or trials for depression, and/orexercise or dietary programs, among other advertisements. Depression, invarious embodiments, causes tiredness and slow metabolism and results inprescription medication.

Further, in some embodiments, depression causes sleep cycle and eatingproblems. For example, a user that is depressed may stay up late andwhich may result in eating additional snacks. At block 146, in responseto the depression suggestions and/or reports of sleep cycle or eatingissues input to the scale, the scale provides sleep cycle and eatingsuggestions. For example, another user wearable device, in someembodiments, reports the sleep cycle or eating issue to the scale. As aspecific embodiment, a user may wear a user wearable device (e.g.,Fitbit®) to track various data, such as cardiogram data, exercise data,and sleep cycle data. Further, the user inputs eating habits to the userwearable device. The user wearable device, in such embodiments,communicates the sleep cycle and eating habit data to the scale. Thesleep cycle and eating suggestions, in various embodiments, includesuggestions to improve the user's sleep cycle (e.g., indication of hourssleeping, exercise advice, dietary advice, such as a time of the day tostop eating), dietary advice, exercise advice, among other lifestyleadvice (e.g., stop watching television one hour before bed). Sleep cycleand eating issues cause, in various embodiments, the excess weight ofthe user. Further, excess weight is correlated to tiredness and slowmetabolism.

In various embodiments, the scale and various user data is used tomonitor atrial fibrillation (AFIB) of the user and various relatedproblems of AFIB. Various scale-based suggestions and advertisements areprovided to the user, such as using the foot-controlled user interface,to assist in monitoring the user's condition, monitoring symptoms orrelated problems, and educating the user on symptoms, related problems,and the correlation thereof. Further, physician provideddiagnosis/reports data is used to refine the monitoring of the conditionand provide feedback to the user. The excess weight causes and/orincreases the risk, for some users, AFIB. Further, a recent increase inweight that is over a threshold amount can also include an increasedrisk for AFIB. The scale is used to monitor BCG, IPG, PWV, and othercardio-indicators of AFIB (e.g., rhythm disturbance, amplitudevariations in BCG and/or IPG).

FIGS. 19a-c show example impedance as measured through different partsof the foot based on the foot position, consistent with various aspectsof the present disclosure. For instance, example impedance measurementconfigurations may be implemented using a dynamic electrodeconfiguration for measurement of foot impedance and related timings.Dynamic electrode configuration may be implemented usingindependently-configurable electrodes to optimize the impedancemeasurement. As shown in FIG. 19a , interleaved electrodes 1900 areconnected to an impedance processor circuit 1905 to determine footlength, foot position, and/or foot impedance. As is shown in FIG. 19b ,an impedance measurement is determined regardless of foot position 1910based on measurement of the placement of the foot across the electrodes1900. This is based in part in the electrodes 1900 that are engaged(blackened) and in contact with the foot (based on the foot position1910), which is shown in FIG. 19 c.

More specifically regarding FIG. 19a , configuration includesconnection/de-connection of the individual electrodes 1900 to theimpedance processor circuit 1905, their configuration ascurrent-carrying electrodes (injection or return), sense electrodes(positive or negative), or both. The configuration is preset based onuser information, or updated at each measurement (dynamicreconfiguration) to optimize a given parameter (impedance SNR,measurement location). The system algorithmically determines whichelectrodes under the foot to use in order to obtain the highest SNR inthe pulse impedance signal. Such optimization algorithm may includeiteratively switching configurations and measuring the impedance, andselecting the best suited configuration. Alternatively, the systemfirst, through a sequential impedance measurement between eachindividual electrode 1900 and another electrode in contact with the body(such as an electrode in electrode pair 205 on the other foot),determine which electrodes are in contact with the foot. By determiningthe two most apart electrodes, the foot size is determined. Heellocation can be determined in this manner, as can other characteristicssuch as foot arch type. These parameters are used to determineprogrammatically (in an automated manner by CPU/logic circuitry) whichelectrodes are selected for current injection and return (and sensing ifa Kelvin connection issued) to obtain the best foot IPG.

In various embodiments involving the dynamically reconfigurableelectrode array 1900/1905, an electrode array set is selected to measurethe same portion/segment of the foot, irrespective of the foot locationon the array. FIG. 19b illustrates the case of several foot positions ona static array (a fixed set of electrodes are used for measurement atthe heel and plantar/toe areas, with a fixed gap of an inactiveelectrode or insulating material between them). Depending on theposition of the foot, the active electrodes are contacting the foot atdifferent locations, thereby sensing a different volume/segment of thefoot. If the IPG is used by itself (e.g., for heart measurement), suchdiscrepancies may be non-consequential. However, if timings derived fromthe IPG are referred to other timings (e.g., R-wave from the ECG, orspecific timing in the BCG), such as for the calculation of a PTT orPWV, the small shifts in IPG timings due to the sensing of slightlydifferent volumes in the foot (e.g., if the foot is not always placed atthe same position on the electrodes) can introduce an error in thecalculation of the interval. With respect to FIG. 19b , the timing ofthe peak of the IPG from the foot placement on the right (sensing thetoe/plantar region) is later than from the foot placement on the left,which senses more of the heel volume (the pulse reaches first the heel,then the plantar region). Factors influencing the magnitude of thesediscrepancies include foot shape (flat or not) and foot length.

Various embodiments address challenges relating to foot placement. FIG.19c shows an example embodiment involving dynamic reconfiguration of theelectrodes to reduce such foot placement-induced variations. As anexample, by sensing the location of the heel first (as described above),it is possible to activate a subset of electrodes under the heel, andanother subset of electrodes separated by a fixed distance (1900). Theother electrodes (e.g., unused electrodes) are left disconnected. Thesensed volume will therefore be the same, producing consistent timings.The electrode configuration leading to the most consistent results maybe informed by the foot impedance, foot length, the type of arch (all ofwhich can be measured by the electrode array as shown above), but alsoby the user ID (foot information can be stored for each user, thenlooked up based on automatic user recognition or manual selection (e.g.,in a look-up-table stored for each user in a memory circuit accessibleby the CPU circuit in the scale).

In certain embodiments, the apparatus measures impedance using aplurality of electrodes contacting one foot and with at least one otherelectrode (typically many) at a location distal from the foot. Theplurality of electrodes (contacting the one foot) is arranged on theplatform and in a pattern configured to inject current signals and sensesignals in response thereto, for the same segment of the foot so thatthe timing of the pulse-based measurements does not vary because theuser placed the one foot at a slightly different position on theplatform or scale. In FIG. 19a , the foot-to-electrode locations for theheel are different locations than that shown in FIGS. 19b and 19c . Asthis different foot placement can occur from day to day for the user,the timing and related impedance measurements are for the same(internal) segment of the foot. By having the processor circuit injectcurrent and sense responsive signals to first locate the foot on theelectrodes (e.g., sensing where positions of the foot's heel plantarregions and/or toes), the pattern of foot-to-electrode locations permitsthe foot to move laterally, horizontally and both laterally andhorizontally via the different electrode locations, while collectingimpedance measurements relative to the same segment of the foot.

The BCG/IPG system can be used to determine the PTT of the user, byidentification of the average I-Wave or derivative timing near theI-Wave from a plurality of BCG heartbeat signals obtained simultaneouslywith the Dual-IPG measurements of the present disclosure to determinethe relative PTT along an arterial segment between the ascending aorticarch and distal pulse timing of the user's lower extremity. In certainembodiments, the BCG/IPG system is used to determine the PWV of theuser, by identification of the characteristic length representing thelength of the user's arteries, and by identification of the averageI-Wave or derivative timing near the I-Wave from a plurality of BCGheartbeat signals obtained simultaneously with the Dual-IPG measurementsof the present disclosure to determine the relative PTT along anarterial segment between the ascending aortic arch and distal pulsetiming of the user's lower extremity. The system of the presentdisclosure and alternate embodiments may be suitable for determining thearterial stiffness (or arterial compliance) and/or cardiovascular riskof the user regardless of the position of the user's feet within thebounds of the interleaved electrodes. In certain embodiments, theweighing scale system incorporated the use of strain gage load cells andsix or eight electrodes to measure a plurality of signals including:bodyweight, BCG, body mass index, fat percentage, muscle masspercentage, and body water percentage, heart rate, heart ratevariability, PTT, and PWV measured simultaneously or synchronously whenthe user stands on the scale to provide a comprehensive analysis of thehealth and wellness of the user.

In other certain embodiments, the PTT and PWV are computed using timingsfrom the Leg IPG or Foot IPG for arrival times, and using timings from asensor located on the upper body (as opposed to the scale measuring theBCG) to detect the start of the pulse. Such sensor may include animpedance sensor for impedance cardiography, a hand-to-hand impedancesensor, a photoplethysmogram on the chest, neck, head, arms or hands, oran accelerometer on the chest (seismocardiograph) or head.

Communication of the biometric information is another aspect of thepresent disclosure. The biometric results from the user are stored inthe memory on the scale and displayed to the user via a display on thescale, audible communication from the scale, and/or the data iscommunicated to a peripheral device such as a computer, smart phone,tablet computing device. The communication occurs to the peripheraldevice with a wired connection, or can be sent to the peripheral devicethrough wireless communication protocols such as Bluetooth or WiFi.Computations such as signal analyses described therein may be carriedout locally on the scale, in a smartphone or computer, or in a remoteprocessor (cloud computing).

Other aspects of the present disclosure are directed toward apparatusesor methods that include the use of at least two electrodes that contactsfeet of a user. Further, circuitry is provided to determine a pulsearrival time at the foot based on the recording of two or more impedancesignals from the set of electrodes. Additionally, a second set ofcircuitry is provided to extract a first pulse arrival time from a firstimpedance signal and use the first pulse arrival time as a timingreference to extract and process a second pulse arrival time in a secondimpedance signal.

Various embodiments are implemented in accordance with, and fullyincorporating by reference for their general teachings, theabove-identified PCT Applications and U.S. Provisional Applications(including PCT Ser. No. PCT/US2016/062484 and PCT Ser. No.PCT/US2016/062505), which teachings are also incorporated by referencespecifically concerning physiological scales and related measurementsand communications such as exemplified by disclosure in connection withFIGS. 1a, 1b, 1e-1f, and 2b-e PCT Ser. No. PCT/US2016/062484 and FIGS.1a, 1c, 1k, 1m, 1n, 1o, in PCT Ser. No. PCT/US2016/062505, and relateddisclosure in the above-identified U.S. Provisional Applications. Forexample, U.S. Provisional Application (Ser. No. 62/258,253), whichteachings are also incorporated by reference specifically concerningusing a scale to instruct a user to have a particular posture whileobtaining scale-data features and aspects as exemplified by disclosurein connection with FIGS. 1a-1b of the underlying provisional; U.S.Provisional Application (Ser. No. 62/260,174), which teachings are alsoincorporated by reference specifically concerning remotely processingphysiological data and providing generic health information based oncategories of interest features and aspects as described in connectionwith FIGS. 1a-1e in the underlying provisional; and U.S. ProvisionalApplication (Ser. No. 62/266,523), which teachings are also incorporatedby reference specifically concerning grouping users into inter and intrascale social groups based on aggregated user data sets, and providingnormalized user data to other users in the social group aspects asexemplified by disclosure in connection with FIGS. 1a-1c of theunderlying provisional.

For instance, embodiments herein and/or in the PCT and provisionalapplications may be combined in varying degrees (including wholly).Reference may also be made to the experimental teachings and underlyingreferences provided in the PCT and provisional applications. Embodimentsdiscussed in the provisional applicants are not intended, in any way, tobe limiting to the overall technical disclosure, or to any part of theclaimed invention unless specifically noted.

Reference may also be made to published patent documents U.S. PatentPublication 2010/0094147 and U.S. Patent Publication 2013/0310700, whichare, together with the references cited therein, herein fullyincorporated by reference for the purposes of sensors and sensingtechnology. The aspects discussed therein may be implemented inconnection with one or more of embodiments and implementations of thepresent disclosure (as well as with those shown in the figures). In viewof the description herein, those skilled in the art will recognize thatmany changes may be made thereto without departing from the spirit andscope of the present disclosure.

As illustrated herein, various circuit-based building blocks and/ormodules may be implemented to carry out one or more of theoperations/activities described herein shown in the block-diagram-typefigures. In such contexts, these building blocks and/or modulesrepresent circuits that carry out these or relatedoperations/activities. For example, in certain embodiments discussedabove (such as the pulse circuitry modularized as shown in FIGS. 3a-b ),one or more blocks/modules are discrete logic circuits or programmablelogic circuits for implementing these operations/activities, as in thecircuit blocks/modules shown. In certain embodiments, the programmablecircuit is one or more computer circuits programmed to execute a set (orsets) of instructions (and/or configuration data). The instructions(and/or configuration data) can be in the form of firmware or softwarestored in and accessible from a memory circuit. As an example, first andsecond modules/blocks include a combination of a CPU hardware-basedcircuit and a set of instructions in the form of firmware, where thefirst module/block includes a first CPU hardware circuit with one set ofinstructions and the second module/block includes a second CPU hardwarecircuit with another set of instructions.

Based upon the above discussion and illustrations, those skilled in theart will readily recognize that the above described aspects andfeatures, and without limitation to the number thereof, can be combinedin specific designs so that the scale is configured and arranged toperform these aspects and features in combination in a manner consistentwith the description thereof. Further, based upon the above discussionand illustrations, those skilled in the art will readily recognize thatvarious modifications and changes may be made to the present disclosurewithout strictly following the exemplary embodiments and applicationsillustrated and described herein. For example, the input terminals asshown and discussed may be replaced with terminals of differentarrangements, and different types and numbers of input configurations(e.g., involving different types of input circuits and relatedconnectivity). Such modifications do not depart from the true spirit andscope of the present disclosure, including that set forth in thefollowing claims.

What is claimed is:
 1. An apparatus including: a scale comprising: a user display configured to display data to a user, a platform configured for the user to stand on, data-procurement circuitry, including force sensor circuitry and a plurality of electrodes integrated with the platform, and configured to engage the user with electrical signals and collect signals indicative of an identity of the user and cardio-physiological measurements while the user is standing on the platform, and processing circuitry, including a central processing unit (CPU) and a memory circuit with user-corresponding data, configured with the data-procurement circuitry to process data obtained by the data-procurement circuitry while the user is standing on the platform and therefrom generate cardio-related physiologic data and determine the identity of the user, the processing circuitry further configured to determine activation of a scale-data based service for the user based on the determined identity of the user, the scale-data based service related to providing additional health information correlated to the user and categories of interest associated with the user including user demographic data and including disorder or symptom data of the user, wherein the disorder or symptom data is derived from the generated cardio-related physiologic data; and an output circuit configured to receive user data and, in response to the determined activation of the scale-data based service for the user, send the user data, including data indicative of the user's identity and the generated cardio-related physiologic data, from the scale for reception at a remote location, and further configured to display, on the user display, a weight of the user and at least a portion of the generated cardio-related physiologic data; and external circuitry configured to: receive and validate the user data as concerning the user associated with a user identifier (ID) and determine at least one physiologic parameter of the user using the user data; and derive the additional health information corresponding to the user data based on the categories of interest and output the additional health information to the scale for display on the user display or for communication by the scale for display on a user device in communication with the scale, wherein the external circuitry is to communicate with the processing circuitry and is to receive the user data, and instruct the scale to ask for the categories of interest, and then correlate the user data with the categories of interest.
 2. The apparatus of claim 1, wherein the processing circuitry determines identification of the user and a corresponding user ID based on biometric data obtained from the user while the user is standing on the platform.
 3. The apparatus of claim 2, wherein the scale further includes a speaker component configured and arranged to capture voice sounds from the user and the data indicative of the identity of the user includes voice sounds captured by the speaker component.
 4. The apparatus of claim 1, wherein the data-procurement circuitry and the processing circuitry are further configured and arranged to activate the scale-data based service by providing a number of questions to the user including: asking if the user is interested in the additional health information; and asking the user for the categories of interest.
 5. The apparatus of claim 1, wherein the data-procurement circuitry and the processing circuitry are further configured and arranged to provide a number of questions to the user including asking the user if the user has a symptom occurring and to activate the scale-data based service in response to answers to the questions.
 6. An apparatus including: a scale comprising: a user display configured and arranged to display data to a user, a platform configured and arranged for the user to stand on, data-procurement circuitry, including force sensor circuitry and a plurality of electrodes integrated with the platform, and configured and arranged to engage the user with electrical signals and collect signals indicative of an identity of the user and cardio-physiological measurements while the user is standing on the platform, and processing circuitry, including a central processing unit (CPU) and a memory circuit with user-corresponding data, configured and arranged with the data-procurement circuitry to process data obtained by the data-procurement circuitry while the user is standing on the platform and therefrom generate cardio-related physiologic data and determine the identity of the user, the processing circuitry further configured and arranged to determine activation of a scale-data based service for the user based on the determined identity of the user, the scale-data based service related to providing additional health information correlated to the user and categories of interest associated with the user including user demographic data and including disorder or symptom data of the user, wherein the disorder or symptom data is derived from the generated cardio-related physiologic data; and an output circuit configured and arranged to receive user data and, in response to the determined activation of the scale-data based service for the user, send the user data, including data indicative of the user's identity and the generated cardio-related physiologic data, from the scale for reception at a remote location, and further configured and arranged to display, on the user display, a weight of the user and at least a portion of the generated cardio-related physiologic data; and external circuitry configured to: receive and validate the user data as concerning the user associated with a user identifier (ID) and determine at least one physiologic parameter of the user using the user data; and derive the additional health information corresponding to the user data based on the categories of interest and output the additional health information to the scale for display on the user display or for communication by the scale for display on a user device in communication with the scale, wherein the external circuitry is configured and arranged to: receive the user data; instruct the scale to ask for the categories of interest; and in response to receiving the categories of interest from the scale, correlate the user data with the categories of interest and, therefrom, derive the additional health information.
 7. The apparatus of claim 1, wherein the external circuitry includes an output circuit configured and arranged to receive the at least one physiologic parameter and, in response, send the at least one physiologic parameter to the scale, wherein the processing circuitry and the user display are configured and arranged to, responsive to receiving the at least one physiologic parameter from the external circuitry, display the at least one physiologic parameter to the user.
 8. The apparatus of claim 1, wherein the external circuitry is configured and arranged to allow access to the at least one physiologic parameter to a physician corresponding with the user and not allow access to the at least one physiologic parameter to the user.
 9. A method comprising: engaging a user, via a scale, with electrical signals and, therefrom, collecting signals indicative of the user's identity while the user is standing on a platform of the scale, wherein the scale includes: a user display, the platform configured and arranged for the user to stand on, data-procurement circuitry, including force sensor circuitry and a plurality of electrodes integrated with the platform, processing circuitry being electrically integrated with the force sensor circuitry and the plurality of electrodes, and an output circuit; processing, using the processing circuitry, data obtained by the data-procurement circuitry while the user is standing on the platform and therefrom generating cardio-related physiologic data corresponding to the collected signals; displaying a weight of the user on the user display; determining an identity of the user from the data obtained by the data-procurement circuitry and, based on the identity of the user, determining activation of a scale-data based service for the user, the scale-data based service related to providing additional health information correlated to the user and categories of interest associated with the user including user demographic data and including disorder or symptom data of the user, wherein the disorder or symptom data is derived from the generated cardio-related physiologic data; outputting, using the output circuit, user data including data indicative of the identity of the user and the generated cardio-related physiologic data in response to the determined activation of the scale-data based service for the user, from the scale for reception by external circuitry at a remote location; validating the user data as concerning the user associated with a user identifier (ID); determining, using the external circuitry, at least one physiologic parameter of the user using the user data; deriving the additional health information for the user by correlating the categories of interest to the at least one physiologic parameter; and outputting the additional health information to the scale or a user device associated with the user and in communication with the scale for display, wherein the external circuitry is to: receive the user data; instruct the scale to ask for the categories of interest; and in response to receiving the categories of interest from the scale, correlate the user data with the categories of interest and, therefrom, derive the additional health information.
 10. The method of claim 9, wherein correlating the categories of interest to the at least one physiologic parameter includes comparing statistical data of a sample census pertinent to the categories of interest and the at least one physiologic parameter.
 11. The method of claim 9, wherein correlating the categories of interest to the at least one physiologic parameter includes comparing statistical data of a sample census pertinent to the categories of interest and values of the at least one physiologic parameter of the sample census.
 12. The method of claim 9, further including: outputting the at least one of the physiologic parameter and the additional health information to the scale; and responsive to receiving the at least one of the physiologic parameter and the additional health information from the external circuitry, displaying the at least one of the physiologic parameter and the additional health information to the user via a user display of the scale.
 13. The method of claim 9, further including querying the user, using the scale, for the categories of interest and outputting the categories of interest to the external circuitry.
 14. The method of claim 9, further include providing the additional health information to the user, via the scale, wherein the additional health information includes average physiologic parameter values of a sample census that is set by the user via the categories of interest.
 15. The apparatus of claim 1, wherein the scale is updated with the additional health information communicated from the external circuitry.
 16. The apparatus of claim 1, wherein the external circuitry is further configured and arranged to determine the at least one physiologic parameter using the physiologic parameter, the at least one physiologic parameter being included in the additional health information, and the scale is updated with the additional health information communicated from the external circuitry.
 17. The apparatus of claim 1, wherein the scale is used by a plurality of users including at least the user and one other user, the processing circuitry is further configured and arranged to identify the user from the other of the plurality of users, and in response, determine the activation of the scale-data based service for at least the user of the plurality of users based on the identity of the user.
 18. The apparatus of claim 17, wherein the processing circuitry is configured and arranged to identify each of the plurality of users from one another, and in response, to determine which of the plurality of users has activated the scale-data based service associated with additional health information, and the output circuit is configured and arranged with the processing circuitry to selectively output subsets of the respective user data in response to determining the activation of the scale-data based service for selective ones of the plurality of users, the selective ones including at least the user of the plurality of users.
 19. The apparatus of claim 1, wherein the scale is used by a plurality of users including at least the user and one other user, the scale being configured and arranged to operate in different modes of data communication for the plurality of users including a medical professional mode and a scale-user mode, and depending on activation of the scale-data based service and which of the different modes is being operated, the scale is to send the user data to the external circuitry for generating the additional health information.
 20. The apparatus of claim 19, wherein the scale is updated with the additional health information communicated from the external circuitry to revise the scale for the user. 